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alexander kudryavtsev

https://en.wikipedia.org/wiki/Alexander_Kudryavtsev

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18621753-7.html.csv

count

on 5 different occasions , alexander kudryavtsev partnered with alexander krasnorutskiy against their opponents .

{'scope': 'all', 'criterion': 'equal', 'value': 'alexander krasnorutskiy', 'result': '5', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'partner', 'alexander krasnorutskiy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose partner record fuzzily matches to alexander krasnorutskiy .', 'tostr': 'filter_eq { all_rows ; partner ; alexander krasnorutskiy }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; partner ; alexander krasnorutskiy } }', 'tointer': 'select the rows whose partner record fuzzily matches to alexander krasnorutskiy . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; partner ; alexander krasnorutskiy } } ; 5 } = true', 'tointer': 'select the rows whose partner record fuzzily matches to alexander krasnorutskiy . the number of such rows is 5 .'}

eq { count { filter_eq { all_rows ; partner ; alexander krasnorutskiy } } ; 5 } = true

select the rows whose partner record fuzzily matches to alexander krasnorutskiy . the number of such rows is 5 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'partner_5': 5, 'alexander krasnorutskiy_6': 6, '5_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'partner_5': 'partner', 'alexander krasnorutskiy_6': 'alexander krasnorutskiy', '5_7': '5'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'partner_5': [0], 'alexander krasnorutskiy_6': [0], '5_7': [2]}

['date', 'tournament', 'surface', 'partner', 'opponent in final', 'score']

[['11 july 2004', 'oberstaufen , germany', 'clay', 'vadim davletshin', 'valentino pest alexander waske', '4 - 6 , 6 - 3 , 7 - 6'], ['27 may 2006', 'kiev , ukraine', 'clay', 'alexander krasnorutskiy', 'andrei stoliarov aleksandr yarmola', '6 - 3 , 3 - 6 , 6 - 2'], ['4 june 2006', 'cherkasy , ukraine', 'clay', 'alexander krasnorutskiy', 'sergei bubka aleksandr nedovesov', '6 - 3 , 4 - 6 , 6 - 2'], ['25 june 2006', 'minsk , belarus', 'hard', 'alexander krasnorutskiy', 'alexander bury kyril harbatsiuk', '7 - 5 , 6 - 3'], ['27 august 2006', 'poznań , poland', 'clay', 'alexander krasnorutskiy', 'tomasz bednarek maciej dilaj', '2 - 6 , 7 - 5 , 6 - 1'], ['26 november 2006', 'mosrentgen , russia', 'hard', 'alexander krasnorutskiy', 'sarvar ikramov alexey tikhonov', '6 - 1 , 6 - 1'], ['20 august 2011', 'karshi , kazakhstan', 'hard', 'michail elgin', 'konstantin kravchuk denys molchanov', '3 - 6 , 6 - 3 ,'], ['6 november 2011', 'eckental , germany', 'carpet', 'andre begemann', 'james cerretani adil shamasdin', '6 - 3 , 3 - 6 ,']]

kingco athletic conference

https://en.wikipedia.org/wiki/Kingco_Athletic_Conference

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13759592-2.html.csv

superlative

the highest amount of enrollments was attributed to the mercer island institution in the kingco athletic conference .

{'scope': 'all', 'col_superlative': '5', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'enrollment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; enrollment }'}, 'location'], 'result': 'mercer island', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; enrollment } ; location }'}, 'mercer island'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; enrollment } ; location } ; mercer island } = true', 'tointer': 'select the row whose enrollment record of all rows is maximum . the location record of this row is mercer island .'}

eq { hop { argmax { all_rows ; enrollment } ; location } ; mercer island } = true

select the row whose enrollment record of all rows is maximum . the location record of this row is mercer island .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'enrollment_5': 5, 'location_6': 6, 'mercer island_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'enrollment_5': 'enrollment', 'location_6': 'location', 'mercer island_7': 'mercer island'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'enrollment_5': [0], 'location_6': [1], 'mercer island_7': [2]}

['institution', 'location', 'founded', 'affiliation', 'enrollment', 'nickname']

[['bellevue', 'bellevue', '1923', 'public ( bellevue sd )', '1327', 'wolverines'], ['interlake', 'bellevue', '1968', 'public ( bellevue sd )', '1341', 's saint'], ['juanita', 'kirkland', '1971', 'public ( lake washington sd )', '1010', 'rebels'], ['liberty', 'renton', '1977', 'public ( issaquah sd )', '1237', 'patriots'], ['mercer island', 'mercer island', '1957', 'public ( mercer island sd )', '1424', 'ers island']]

1965 american football league draft

https://en.wikipedia.org/wiki/1965_American_Football_League_Draft

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18652198-3.html.csv

unique

allen brown is the only player who was drafted from mississippi .

{'scope': 'all', 'row': '6', 'col': '5', 'col_other': '3', 'criterion': 'equal', 'value': 'mississippi', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'mississippi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to mississippi .', 'tostr': 'filter_eq { all_rows ; college ; mississippi }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; college ; mississippi } }', 'tointer': 'select the rows whose college record fuzzily matches to mississippi . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'college', 'mississippi'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose college record fuzzily matches to mississippi .', 'tostr': 'filter_eq { all_rows ; college ; mississippi }'}, 'player'], 'result': 'allen brown', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; college ; mississippi } ; player }'}, 'allen brown'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; college ; mississippi } ; player } ; allen brown }', 'tointer': 'the player record of this unqiue row is allen brown .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; college ; mississippi } } ; eq { hop { filter_eq { all_rows ; college ; mississippi } ; player } ; allen brown } } = true', 'tointer': 'select the rows whose college record fuzzily matches to mississippi . there is only one such row in the table . the player record of this unqiue row is allen brown .'}

and { only { filter_eq { all_rows ; college ; mississippi } } ; eq { hop { filter_eq { all_rows ; college ; mississippi } ; player } ; allen brown } } = true

select the rows whose college record fuzzily matches to mississippi . there is only one such row in the table . the player record of this unqiue row is allen brown .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'college_7': 7, 'mississippi_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'allen brown_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'college_7': 'college', 'mississippi_8': 'mississippi', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'allen brown_10': 'allen brown'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'college_7': [0], 'mississippi_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'allen brown_10': [3]}

['pick', 'team', 'player', 'position', 'college']

[['17', 'denver broncos', 'glenn ressler', 'offensive guard', 'penn state'], ['18', 'houston oilers', 'ernie koy', 'running back', 'texas'], ['19', 'oakland raiders', 'bob svihus', 'defensive tackle', 'usc'], ['20', 'new york jets', 'verlon biggs', 'defensive end', 'jackson state'], ['21', 'kansas city chiefs', 'mike curtis', 'linebacker', 'duke'], ['22', 'san diego chargers', 'allen brown', 'tight end', 'mississippi'], ['23', 'boston patriots', 'jim whalen', 'tackle', 'boston college'], ['24', 'buffalo bills', 'al atkinson', 'linebacker', 'villanova']]

the rob brydon show

https://en.wikipedia.org/wiki/The_Rob_Brydon_Show

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29135051-3.html.csv

count

5 singers were invited on the the rob brydon show in 2012 .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '5', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'singer ( s )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose singer ( s ) record is arbitrary .', 'tostr': 'filter_all { all_rows ; singer ( s ) }'}], 'result': '5', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; singer ( s ) } }', 'tointer': 'select the rows whose singer ( s ) record is arbitrary . the number of such rows is 5 .'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; singer ( s ) } } ; 5 } = true', 'tointer': 'select the rows whose singer ( s ) record is arbitrary . the number of such rows is 5 .'}

eq { count { filter_all { all_rows ; singer ( s ) } } ; 5 } = true

select the rows whose singer ( s ) record is arbitrary . the number of such rows is 5 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'singer (s)_5': 5, '5_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'singer (s)_5': 'singer ( s )', '5_6': '5'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'singer (s)_5': [0], '5_6': [2]}

['episode', 'broadcast date', 'guest ( s )', 'singer ( s )', 'ratings']

[['1', '14 august 2012', 'michael mcintyre and alex james', 'amy macdonald', '1.44 m'], ['2', '21 august 2012', 'barbara windsor and heston blumenthal', 'the overtones', 'under 1.39 m'], ['3', '28 august 2012', 'sarah millican and grayson perry', 'newton faulkner', 'under 1.39 m'], ['4', '4 september 2012', 'jason manford and neil morrissey', 'ronan keating', 'under 1.25 m'], ['5', '11 september 2012', 'emilia fox and steve backshall', 'tom jones', 'under 1.37 m']]

porsche boxster

https://en.wikipedia.org/wiki/Porsche_Boxster

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24729-2.html.csv

count

three of versions of the porsche boxster listed have a 2.7 litre engine .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': '2.7', 'result': '3', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'engine', '2.7'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose engine record fuzzily matches to 2.7 .', 'tostr': 'filter_eq { all_rows ; engine ; 2.7 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; engine ; 2.7 } }', 'tointer': 'select the rows whose engine record fuzzily matches to 2.7 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; engine ; 2.7 } } ; 3 } = true', 'tointer': 'select the rows whose engine record fuzzily matches to 2.7 . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; engine ; 2.7 } } ; 3 } = true

select the rows whose engine record fuzzily matches to 2.7 . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'engine_5': 5, '2.7_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'engine_5': 'engine', '2.7_6': '2.7', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'engine_5': [0], '2.7_6': [0], '3_7': [2]}

['year', 'engine', 'power', 'torque', 'transmission', '0 - 100 km / h ( 60 mph )', 'top speed', 'co2']

[['2012', '2.7 l ( 2706 cc )', 'n / a', '', 'manual ( 6 )', '5.8 seconds ( 5.5 )', 'n / a', '192 g / km'], ['2012', '2.7 l ( 2706 cc )', 'n / a', '', 'pdk ( 7 )', '5.7 seconds ( 5.4 )', 'n / a', '180 g / km'], ['2012', '2.7 l ( 2706 cc ) sport chrono', 'n / a', '', 'pdk ( 7 )', '5.5 seconds ( 5.2 )', 'n / a', '180 g / km'], ['2012', '3.4 l ( 3436 cc )', 'n / a', '', 'manual ( 6 )', '5.1 seconds ( 4.8 )', 'n / a', '206 g / km'], ['2012', '3.4 l ( 3436 cc )', 'n / a', '', 'pdk ( 7 )', '5.0 seconds ( 4.7 )', 'n / a', '188 g / km']]

list of england national rugby union team results 2000 - 09

https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_2000%E2%80%9309

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178551-6.html.csv

ordinal

in the england national rugby union team results for 2000 - 09 , the 2nd highest against was when the opposing team was scotland .

{'row': '5', 'col': '2', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'against', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; against ; 2 }'}, 'opposing teams'], 'result': 'scotland', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; against ; 2 } ; opposing teams }'}, 'scotland'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; against ; 2 } ; opposing teams } ; scotland } = true', 'tointer': 'select the row whose against record of all rows is 2nd maximum . the opposing teams record of this row is scotland .'}

eq { hop { nth_argmax { all_rows ; against ; 2 } ; opposing teams } ; scotland } = true

select the row whose against record of all rows is 2nd maximum . the opposing teams record of this row is scotland .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'against_5': 5, '2_6': 6, 'opposing teams_7': 7, 'scotland_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'against_5': 'against', '2_6': '2', 'opposing teams_7': 'opposing teams', 'scotland_8': 'scotland'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'against_5': [0], '2_6': [0], 'opposing teams_7': [1], 'scotland_8': [2]}

['opposing teams', 'against', 'date', 'venue', 'status']

[['wales', '11', '05 / 02 / 2005', 'millennium stadium , cardiff', 'six nations'], ['france', '18', '13 / 02 / 2005', 'twickenham , london', 'six nations'], ['ireland', '19', '27 / 02 / 2005', 'lansdowne road , dublin', 'six nations'], ['italy', '7', '12 / 03 / 2005', 'twickenham , london', 'six nations'], ['scotland', '22', '19 / 03 / 2005', 'twickenham , london', 'six nations'], ['australia', '16', '12 / 11 / 2005', 'twickenham , london', 'test match'], ['new zealand', '23', '19 / 11 / 2005', 'twickenham , london', 'test match'], ['samoa', '3', '26 / 11 / 2005', 'twickenham , london', 'test match']]

los angeles lakers all - time roster

https://en.wikipedia.org/wiki/Los_Angeles_Lakers_all-time_roster

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10560886-12.html.csv

ordinal

jim krebs is the third earliest player to join the los angeles lakers all - time roster .

{'row': '12', 'col': '4', 'order': '3', 'col_other': '1', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'from', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; from ; 3 }'}, 'player'], 'result': 'jim krebs', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; from ; 3 } ; player }'}, 'jim krebs'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; from ; 3 } ; player } ; jim krebs } = true', 'tointer': 'select the row whose from record of all rows is 3rd minimum . the player record of this row is jim krebs .'}

eq { hop { nth_argmin { all_rows ; from ; 3 } ; player } ; jim krebs } = true

select the row whose from record of all rows is 3rd minimum . the player record of this row is jim krebs .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'from_5': 5, '3_6': 6, 'player_7': 7, 'jim krebs_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'from_5': 'from', '3_6': '3', 'player_7': 'player', 'jim krebs_8': 'jim krebs'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'from_5': [0], '3_6': [0], 'player_7': [1], 'jim krebs_8': [2]}

['player', 'nationality', 'position', 'from', 'school / country']

[['edwin kachan', 'united states', 'guard', '1948', 'depaul'], ['ed kalafat', 'united states', 'forward / center', '1954', 'minnesota'], ['jason kapono', 'united states', 'forward', '2011', 'ucla'], ['coby karl', 'united states', 'guard', '2007', 'boise state'], ['jerome kersey', 'united states', 'forward', '1996', 'longwood'], ['randolph keys', 'united states', 'guard / forward', '1994', 'southern mississippi'], ['earnie killum', 'united states', 'guard', '1970', 'stetson'], ['frankie king', 'united states', 'guard', '1995', 'western carolina'], ['jim king', 'united states', 'guard', '1963', 'tulsa'], ['joe kleine', 'united states', 'center', '1996', 'arkansas'], ['travis knight', 'united states', 'forward / center', '1996 , 1999', 'connecticut'], ['jim krebs', 'united states', 'forward / center', '1957', 'southern methodist'], ['larry krystkowiak', 'united states', 'forward / center', '1996', 'montana'], ['mitch kupchak', 'united states', 'forward / center', '1981', 'north carolina'], ['cj kupec', 'united states', 'forward / center', '1975', 'michigan']]

will & grace ( season 5 )

https://en.wikipedia.org/wiki/Will_%26_Grace_%28season_5%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27833469-1.html.csv

count

adam barr wrote a total of two episodes during this season .

{'scope': 'all', 'criterion': 'equal', 'value': 'adam barr', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'written by', 'adam barr'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose written by record fuzzily matches to adam barr .', 'tostr': 'filter_eq { all_rows ; written by ; adam barr }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; written by ; adam barr } }', 'tointer': 'select the rows whose written by record fuzzily matches to adam barr . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; written by ; adam barr } } ; 2 } = true', 'tointer': 'select the rows whose written by record fuzzily matches to adam barr . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; written by ; adam barr } } ; 2 } = true

select the rows whose written by record fuzzily matches to adam barr . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'written by_5': 5, 'adam barr_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'written by_5': 'written by', 'adam barr_6': 'adam barr', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'adam barr_6': [0], '2_7': [2]}

['series', 'season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']

[['93', '1', 'and the horse he rode in on', 'james burrows', 'adam barr', 'september 26 , 2002', '21.5'], ['94', '2', 'bacon and eggs', 'james burrows', 'alex herschlag', 'october 3 , 2002', '20.6'], ['95', '3', 'the kid stays out of the picture', 'james burrows', 'jhoni marchinko', 'october 10 , 2002', '20.2'], ['96', '4', 'humongous growth', 'james burrows', 'kari lizer', 'october 17 , 2002', '19.5'], ['97', '5', "it 's the gay pumpkin , charlie brown", 'james burrows', 'gary janetti', 'october 31 , 2002', '17.2'], ['98', '6', 'boardroom and a parked place', 'james burrows', 'gail lerner', 'november 7 , 2002', '21.1'], ['99', '7', "the needle and the omelet 's done", 'james burrows', 'tracy poust & jon kinnally', 'november 14 , 2002', '19.1'], ['100', '8 - 9', 'marry me a little , marry me a little more', 'james burrows', 'jeff greenstein & bill wrubel', 'november 21 , 2002', '24.3'], ['101', '10', "the honeymoon 's over", 'james burrows', 'sally bradford', 'december 5 , 2002', '19.3'], ['102', '11', 'all about christmas eve', 'james burrows', 'adam barr', 'december 12 , 2002', '16.2'], ['103', '12', 'field of queens', 'james burrows', 'katie palmer', 'january 9 , 2003', '16.2'], ['104', '13', 'fagmalion part i : gay it forward', 'james burrows', 'tracy poust & jon kinnally', 'january 16 , 2003', '16.0'], ['105', '14', 'fagmalion part ii : attack of the clones', 'james burrows', 'gary janetti', 'january 30 , 2003', '15.8'], ['106', '15', 'homojo', 'james burrows', 'bill wrubel', 'february 6 , 2003', '16.5'], ['107', '16', 'women and children first', 'james burrows', 'laura kightlinger', 'february 13 , 2003', '18.7'], ['108', '17', 'fagmalion part iii : bye , bye , beardy', 'james burrows', 'alex herschlag', 'february 20 , 2003', '16.4'], ['109', '18', 'fagmalion part iv : the guy who loved me', 'james burrows', 'gail lerner', 'march 13 , 2003', '15.0'], ['110', '19', 'sex , losers , and videotape', 'james burrows', 'steve gabriel', 'april 3 , 2003', '15.0'], ['111', '20', 'leo unwrapped', 'james burrows', 'sonja warfield', 'april 17 , 2003', '14.7'], ['112', '21', 'dolls and dolls', 'james burrows', 'kari lizer', 'april 24 , 2003', '17.7']]

1999 denver broncos season

https://en.wikipedia.org/wiki/1999_Denver_Broncos_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17990473-1.html.csv

ordinal

the denver broncos game on october 31 , 1999 had the 3rd highest attendance .

{'row': '8', 'col': '5', 'order': '3', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'attendance', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 3 }'}, 'date'], 'result': 'october 31 , 1999', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; date }'}, 'october 31 , 1999'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; october 31 , 1999 } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the date record of this row is october 31 , 1999 .'}

eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; october 31 , 1999 } = true

select the row whose attendance record of all rows is 3rd maximum . the date record of this row is october 31 , 1999 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '3_6': 6, 'date_7': 7, 'october 31 , 1999_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '3_6': '3', 'date_7': 'date', 'october 31 , 1999_8': 'october 31 , 1999'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '3_6': [0], 'date_7': [1], 'october 31 , 1999_8': [2]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 13 , 1999', 'miami dolphins', 'l 38 - 21', '75623'], ['2', 'september 19 , 1999', 'kansas city chiefs', 'l 26 - 10', '78683'], ['3', 'september 26 , 1999', 'tampa bay buccaneers', 'l 13 - 10', '65297'], ['4', 'october 3 , 1999', 'new york jets', 'l 21 - 13', '74181'], ['5', 'october 10 , 1999', 'oakland raiders', 'w 16 - 13', '55704'], ['6', 'october 17 , 1999', 'green bay packers', 'w 31 - 10', '73352'], ['7', 'october 24 , 1999', 'new england patriots', 'l 24 - 23', '60011'], ['8', 'october 31 , 1999', 'minnesota vikings', 'l 23 - 20', '75021'], ['9', 'november 7 , 1999', 'san diego chargers', 'w 33 - 17', '61204'], ['10', 'november 14 , 1999', 'seattle seahawks', 'l 20 - 17', '66314'], ['11', 'november 22 , 1999', 'oakland raiders', 'w 27 - 21', '70012'], ['13', 'december 5 , 1999', 'kansas city chiefs', 'l 16 - 10', '73855'], ['14', 'december 13 , 1999', 'jacksonville jaguars', 'l 27 - 24', '71357'], ['15', 'december 19 , 1999', 'seattle seahawks', 'w 36 - 30', '65987'], ['16', 'december 25 , 1999', 'detroit lions', 'w 17 - 7', '73158'], ['17', 'january 2 , 2000', 'san diego chargers', 'l 12 - 6', '69278']]

heikki kovalainen

https://en.wikipedia.org/wiki/Heikki_Kovalainen

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1527343-1.html.csv

unique

heikki kovalainen only competed in one gp2 series race .

{'scope': 'all', 'row': '10', 'col': '2', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'gp2 series', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'series', 'gp2 series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose series record fuzzily matches to gp2 series .', 'tostr': 'filter_eq { all_rows ; series ; gp2 series }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; series ; gp2 series } } = true', 'tointer': 'select the rows whose series record fuzzily matches to gp2 series . there is only one such row in the table .'}

only { filter_eq { all_rows ; series ; gp2 series } } = true

select the rows whose series record fuzzily matches to gp2 series . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'series_4': 4, 'gp2 series_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'series_4': 'series', 'gp2 series_5': 'gp2 series'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'series_4': [0], 'gp2 series_5': [0]}

['season', 'series', 'team', 'races', 'wins', 'poles', 'f / laps', 'podiums', 'points', 'position']

[['2001', 'formula renault 2000 uk', 'fortec motorsport', '13', '2', '2', '3', '5', '243', '4th'], ['2001', 'macau grand prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '8th'], ['2001', 'korea super prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '25th'], ['2002', 'british formula three', 'fortec motorsport', '26', '5', '2', '3', '12', '257', '3rd'], ['2002', 'macau grand prix', 'fortec motorsport', '1', '0', '0', '0', '1', 'n / a', '2nd'], ['2002', 'korea super prix', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '14th'], ['2002', 'masters of formula 3', 'fortec motorsport', '1', '0', '0', '0', '0', 'n / a', '4th'], ['2003', 'world series by nissan', 'gabord competiciã cubicn', '18', '1', '3', '1', '4', '134', '2nd'], ['2004', 'world series by nissan', 'pons racing', '18', '6', '10', '8', '11', '176', '1st'], ['2005', 'gp2 series', 'arden international', '23', '5', '2', '1', '12', '105', '2nd'], ['2006', 'formula one', 'mild seven renault f1 team', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver'], ['2007', 'formula one', 'ing renault f1 team', '17', '0', '0', '0', '1', '30', '7th'], ['2008', 'formula one', 'vodafone mclaren mercedes', '18', '1', '1', '2', '3', '53', '7th'], ['2009', 'formula one', 'vodafone mclaren mercedes', '17', '0', '0', '0', '0', '22', '12th'], ['2010', 'formula one', 'lotus racing', '19', '0', '0', '0', '0', '0', '20th'], ['2011', 'formula one', 'team lotus', '19', '0', '0', '0', '0', '0', '22nd'], ['2012', 'formula one', 'caterham f1 team', '20', '0', '0', '0', '0', '0', '22nd'], ['2013', 'formula one', 'caterham f1 team', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver', 'test driver']]

list of the amanda show episodes

https://en.wikipedia.org/wiki/List_of_The_Amanda_Show_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17152787-3.html.csv

count

two of these episodes of the amanda show aired in december 2000 .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'december', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'original air date', 'december'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose original air date record fuzzily matches to december .', 'tostr': 'filter_eq { all_rows ; original air date ; december }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; original air date ; december } }', 'tointer': 'select the rows whose original air date record fuzzily matches to december . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; original air date ; december } } ; 2 } = true', 'tointer': 'select the rows whose original air date record fuzzily matches to december . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; original air date ; december } } ; 2 } = true

select the rows whose original air date record fuzzily matches to december . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'original air date_5': 5, 'december_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', 'december_6': 'december', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'original air date_5': [0], 'december_6': [0], '2_7': [2]}

['series', 'season', 'title', 'directed by', 'original air date', 'prod code']

[['14', '1', 'episode 14', 'rich correll , virgil l fabian & ken whittingham', 'july 15 , 2000', '214'], ['16', '3', 'episode 16', 'virgil l fabian & ken whittingham', 'august 12 , 2000', '216'], ['17', '4', 'episode 17', 'virgil l fabian & ken whittingham', 'august 26 , 2000', '217'], ['18', '5', 'episode 18', "tim o'donnell , rich correll & virgil l fabian", 'september 9 , 2000', '218'], ['19', '6', 'episode 19', 'rich correll & virgil l fabian', 'september 23 , 2000', '219'], ['20', '7', 'episode 20', 'rich correll , virgil l fabian & ken whittingham', 'october 7 , 2000', '220'], ['21', '8', 'episode 21', "rich correll , virgil l fabian & tim o'donnell", 'october 21 , 2000', '221'], ['22', '9', 'episode 22', 'rich correll , virgil l fabian & ken whittingham', 'october 28 , 2000', '222'], ['23', '10', 'episode 23', 'rich correll , virgil l fabian & ken whittingham', 'november 18 , 2000', '223'], ['24', '11', 'episode 24', "rich correll , virgil l fabian & tim o'donnell", 'december 9 , 2000', '224'], ['25', '12', 'episode 25', 'rich correll & virgil l fabian', 'december 23 , 2000', '225'], ['26', '13', 'episode 26', 'virgil l fabian & ken whittingham', 'january 27 , 2001', '226'], ['27', '14', 'episode 27', 'rich correll & virgil l fabian', 'february 17 , 2001', '227']]

2004 scottish claymores season

https://en.wikipedia.org/wiki/2004_Scottish_Claymores_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29679510-2.html.csv

unique

in the 2004 scottish claymores season , the game on april 4th was the only one to take place at olympic stadium .

{'scope': 'all', 'row': '1', 'col': '7', 'col_other': '2', 'criterion': 'equal', 'value': 'olympic stadium', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'olympic stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to olympic stadium .', 'tostr': 'filter_eq { all_rows ; game site ; olympic stadium }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; game site ; olympic stadium } }', 'tointer': 'select the rows whose game site record fuzzily matches to olympic stadium . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'olympic stadium'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game site record fuzzily matches to olympic stadium .', 'tostr': 'filter_eq { all_rows ; game site ; olympic stadium }'}, 'date'], 'result': 'sunday , april 4', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game site ; olympic stadium } ; date }'}, 'sunday , april 4'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; game site ; olympic stadium } ; date } ; sunday , april 4 }', 'tointer': 'the date record of this unqiue row is sunday , april 4 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; game site ; olympic stadium } } ; eq { hop { filter_eq { all_rows ; game site ; olympic stadium } ; date } ; sunday , april 4 } } = true', 'tointer': 'select the rows whose game site record fuzzily matches to olympic stadium . there is only one such row in the table . the date record of this unqiue row is sunday , april 4 .'}

and { only { filter_eq { all_rows ; game site ; olympic stadium } } ; eq { hop { filter_eq { all_rows ; game site ; olympic stadium } ; date } ; sunday , april 4 } } = true

select the rows whose game site record fuzzily matches to olympic stadium . there is only one such row in the table . the date record of this unqiue row is sunday , april 4 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'game site_7': 7, 'olympic stadium_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'sunday , april 4_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'game site_7': 'game site', 'olympic stadium_8': 'olympic stadium', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'sunday , april 4_10': 'sunday , april 4'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'game site_7': [0], 'olympic stadium_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'sunday , april 4_10': [3]}

['week', 'date', 'kickoff', 'opponent', 'final score', 'team record', 'game site', 'attendance']

[['1', 'sunday , april 4', '4:00 pm', 'berlin thunder', 'l 14 - 20', '0 - 1', 'olympic stadium', '14257'], ['2', 'saturday , april 10', '7:00 pm', 'rhein fire', 'l 3 - 31', '0 - 2', 'arena aufschalke', '17176'], ['3', 'sunday , april 18', '2:00 pm', 'amsterdam admirals', 'l 0 - 3', '0 - 3', 'hampden park', '10971'], ['4', 'saturday , april 24', '7:00 pm', 'cologne centurions', 'l 3 - 17', '0 - 4', 'rheinenergiestadion', '8761'], ['5', 'sunday , may 2', '2:00 pm', 'rhein fire', 'w 13 - 12', '1 - 4', 'hampden park', '9165'], ['6', 'sunday , may 9', '2:00 pm', 'frankfurt galaxy', 'l 13 - 15', '1 - 5', 'hampden park', '9017'], ['7', 'sunday , may 16', '4:00 pm', 'frankfurt galaxy', 'l 24 - 27', '1 - 6', 'waldstadion', '26879'], ['8', 'friday , may 21', '8:00 pm', 'amsterdam admirals', 'w 19 - 17', '2 - 6', 'amsterdam arena', '10738'], ['9', 'saturday , may 29', '2:00 pm', 'berlin thunder', 'l 19 - 27', '2 - 7', 'hampden park', '9153']]

galatasaray s.k. ( men 's volleyball )

https://en.wikipedia.org/wiki/Galatasaray_S.K._%28men%27s_volleyball%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18729570-2.html.csv

unique

henry bell cisnero is the only player from cuba on the galatasaray s.k. men 's volleyball team .

{'scope': 'all', 'row': '1', 'col': '2', 'col_other': '3', 'criterion': 'equal', 'value': 'cuba', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'cuba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to cuba .', 'tostr': 'filter_eq { all_rows ; nationality ; cuba }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; nationality ; cuba } }', 'tointer': 'select the rows whose nationality record fuzzily matches to cuba . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'nationality', 'cuba'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nationality record fuzzily matches to cuba .', 'tostr': 'filter_eq { all_rows ; nationality ; cuba }'}, 'player'], 'result': 'henry bell cisnero', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; nationality ; cuba } ; player }'}, 'henry bell cisnero'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; nationality ; cuba } ; player } ; henry bell cisnero }', 'tointer': 'the player record of this unqiue row is henry bell cisnero .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; nationality ; cuba } } ; eq { hop { filter_eq { all_rows ; nationality ; cuba } ; player } ; henry bell cisnero } } = true', 'tointer': 'select the rows whose nationality record fuzzily matches to cuba . there is only one such row in the table . the player record of this unqiue row is henry bell cisnero .'}

and { only { filter_eq { all_rows ; nationality ; cuba } } ; eq { hop { filter_eq { all_rows ; nationality ; cuba } ; player } ; henry bell cisnero } } = true

select the rows whose nationality record fuzzily matches to cuba . there is only one such row in the table . the player record of this unqiue row is henry bell cisnero .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'nationality_7': 7, 'cuba_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'henry bell cisnero_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'nationality_7': 'nationality', 'cuba_8': 'cuba', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'henry bell cisnero_10': 'henry bell cisnero'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'nationality_7': [0], 'cuba_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'henry bell cisnero_10': [3]}

['shirt no', 'nationality', 'player', 'birth date', 'height', 'position']

[['6', 'cuba', 'henry bell cisnero', 'july 27 , 1982 ( age31 )', '188', 'spiker'], ['7', 'turkey', 'tolgahan camgöz', 'january 27 , 1990 ( age24 )', '182', 'libero'], ['11', 'turkey', 'caner pekşen', 'june 9 , 1987 ( age26 )', '190', 'setter'], ['15', 'turkey', 'oğuzhan tarakçı', 'april 23 , 1993 ( age20 )', '195', 'outside hitter'], ['16', 'turkey', 'ferhat akdeniz', 'january 14 , 1986 ( age28 )', '203', 'middle blocker']]

jake o'brien

https://en.wikipedia.org/wiki/Jake_O%27Brien

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15985163-2.html.csv

count

4 of jake o'brien 's fights have ended due to submission .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'submission', 'result': '4', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'method', 'submission'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose method record fuzzily matches to submission .', 'tostr': 'filter_eq { all_rows ; method ; submission }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; method ; submission } }', 'tointer': 'select the rows whose method record fuzzily matches to submission . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; method ; submission } } ; 4 } = true', 'tointer': 'select the rows whose method record fuzzily matches to submission . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; method ; submission } } ; 4 } = true

select the rows whose method record fuzzily matches to submission . the number of such rows is 4 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'method_5': 5, 'submission_6': 6, '4_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'method_5': 'method', 'submission_6': 'submission', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'method_5': [0], 'submission_6': [0], '4_7': [2]}

['res', 'record', 'opponent', 'method', 'event', 'round']

[['win', '15 - 4', 'miodrag petković', 'decision ( unanimous )', 'flawless fighting championship 1 : the beginning', '3'], ['win', '14 - 4', 'james shaw', 'submission ( arm - triangle choke )', 'indy mma', '1'], ['loss', '13 - 4', 'gegard mousasi', 'submission ( guillotine choke )', 'dream 15', '1'], ['win', '13 - 3', 'toni valtonen', 'decision ( unanimous )', 'fight festival 27', '3'], ['win', '12 - 3', 'dave hess', 'submission ( kimura )', 'mma big show - triple threat', '2'], ['loss', '11 - 3', 'jon jones', 'submission ( guillotine choke )', 'ufc 100', '2'], ['win', '11 - 2', 'christian wellisch', 'decision ( split )', 'ufc 94', '3'], ['loss', '10 - 2', 'cain velasquez', 'tko ( punches )', 'ufc : silva vs irvin', '1'], ['loss', '10 - 1', 'andrei arlovski', 'tko ( punches )', 'ufc 82', '2'], ['win', '10 - 0', 'heath herring', 'decision ( unanimous )', 'ufc fight night 8', '3'], ['win', '9 - 0', 'josh schockman', 'decision ( unanimous )', 'ufc 65', '3'], ['win', '8 - 0', 'kristof midoux', 'tko ( referee stoppage )', 'ufc fight night 6', '2'], ['win', '7 - 0', 'pat harmon', 'tko', 'ufl - united fight league', '1'], ['win', '6 - 0', 'antoine hayes', 'tko', 'lof - legends of fighting 6', '1'], ['win', '5 - 0', 'jay white', 'ko ( punch )', 'wec 19', '1'], ['win', '4 - 0', 'johnathan ivey', 'tko', 'lof - legends of fighting 4', '1'], ['win', '3 - 0', 'anthony ferguson', 'tko', 'lof - revolution', '1'], ['win', '2 - 0', 'paul bowers', 'tko', 'ifc - integrated fighting classic 3', '1'], ['win', '1 - 0', 'chris clark', 'tko ( referee stoppage )', 'mt - madtown throwdown 3', '1']]

1988 houston oilers season

https://en.wikipedia.org/wiki/1988_Houston_Oilers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15986322-1.html.csv

count

the houston oilers won three of the games they played in the month of november , during the 1988 season .

{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': 'w', 'result': '3', 'col': '4', 'subset': {'col': '2', 'criterion': 'fuzzily_match', 'value': 'november'}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'november'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; november }', 'tointer': 'select the rows whose date record fuzzily matches to november .'}, 'result', 'w'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose result record fuzzily matches to w .', 'tostr': 'filter_eq { filter_eq { all_rows ; date ; november } ; result ; w }'}], 'result': '3', 'ind': 2, 'tostr': 'count { filter_eq { filter_eq { all_rows ; date ; november } ; result ; w } }', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 3, 'tostr': 'eq { count { filter_eq { filter_eq { all_rows ; date ; november } ; result ; w } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to november . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 .'}

eq { count { filter_eq { filter_eq { all_rows ; date ; november } ; result ; w } } ; 3 } = true

select the rows whose date record fuzzily matches to november . among these rows , select the rows whose result record fuzzily matches to w . the number of such rows is 3 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, 'november_7': 7, 'result_8': 8, 'w_9': 9, '3_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', 'november_7': 'november', 'result_8': 'result', 'w_9': 'w', '3_10': '3'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], 'november_7': [0], 'result_8': [1], 'w_9': [1], '3_10': [3]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 4 , 1988', 'indianapolis colts', 'w 17 - 14', '57251'], ['2', 'september 11 , 1988', 'los angeles raiders', 'w 38 - 35', '46050'], ['3', 'september 18 , 1988', 'new york jets', 'l 45 - 3', '64683'], ['4', 'september 25 , 1988', 'new england patriots', 'w 31 - 6', '38646'], ['5', 'october 2 , 1988', 'philadelphia eagles', 'l 32 - 23', '64692'], ['6', 'october 9 , 1988', 'kansas city chiefs', 'w 7 - 6', '39134'], ['7', 'october 16 , 1988', 'pittsburgh steelers', 'w 34 - 14', '52229'], ['8', 'october 23 , 1988', 'cincinnati bengals', 'l 44 - 21', '54659'], ['9', 'october 30 , 1988', 'washington redskins', 'w 41 - 17', '48781'], ['10', 'november 7 , 1988', 'cleveland browns', 'w 24 - 17', '51467'], ['11', 'november 13 , 1988', 'seattle seahawks', 'l 27 - 24', '60446'], ['12', 'november 20 , 1988', 'phoenix cardinals', 'w 38 - 20', '43843'], ['13', 'november 24 , 1988', 'dallas cowboys', 'w 25 - 17', '50845'], ['14', 'december 4 , 1988', 'pittsburgh steelers', 'l 37 - 34', '47791'], ['15', 'december 11 , 1988', 'cincinnati bengals', 'w 41 - 6', '50269'], ['16', 'december 18 , 1988', 'cleveland browns', 'l 28 - 23', '74610']]

peter vagenas

https://en.wikipedia.org/wiki/Peter_Vagenas

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1161885-1.html.csv

aggregation

between his 2000 and 2012 seasons , peter vagenas scored an average of 1 goal per season .

{'scope': 'subset', 'col': '5', 'type': 'average', 'result': '1', 'subset': {'col': '1', 'criterion': 'greater_than_eq', 'value': '2000'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'season', '2000'], 'result': None, 'ind': 0, 'tostr': 'filter_greater_eq { all_rows ; season ; 2000 }', 'tointer': 'select the rows whose season record is greater than or equal to 2000 .'}, 'goals'], 'result': '1', 'ind': 1, 'tostr': 'avg { filter_greater_eq { all_rows ; season ; 2000 } ; goals }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_greater_eq { all_rows ; season ; 2000 } ; goals } ; 1 } = true', 'tointer': 'select the rows whose season record is greater than or equal to 2000 . the average of the goals record of these rows is 1 .'}

round_eq { avg { filter_greater_eq { all_rows ; season ; 2000 } ; goals } ; 1 } = true

select the rows whose season record is greater than or equal to 2000 . the average of the goals record of these rows is 1 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'season_5': 5, '2000_6': 6, 'goals_7': 7, '1_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'season_5': 'season', '2000_6': '2000', 'goals_7': 'goals', '1_8': '1'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'season_5': [0], '2000_6': [0], 'goals_7': [1], '1_8': [2]}

['season', 'club', 'league', 'apps', 'goals']

[['2000', 'los angeles galaxy', 'major league soccer', '16', '3'], ['2001', 'los angeles galaxy', 'major league soccer', '26', '3'], ['2002', 'los angeles galaxy', 'major league soccer', '17', '0'], ['2003', 'los angeles galaxy', 'major league soccer', '20', '0'], ['2004', 'los angeles galaxy', 'major league soccer', '12', '0'], ['2005', 'los angeles galaxy', 'major league soccer', '29', '5'], ['2006', 'los angeles galaxy', 'major league soccer', '25', '2'], ['2007', 'los angeles galaxy', 'major league soccer', '24', '0'], ['2008', 'los angeles galaxy', 'major league soccer', '14', '1'], ['2009', 'seattle sounders fc', 'major league soccer', '14', '0'], ['2010', 'seattle sounders fc', 'major league soccer', '7', '0'], ['2011', 'vancouver whitecaps fc', 'major league soccer', '16', '0'], ['2012', 'chivas usa', 'major league soccer', '1', '0'], ['total', 'last updated : february 22 , 2012', 'last updated : february 22 , 2012', '221', '14']]

2005 - 06 liverpool f.c. season

https://en.wikipedia.org/wiki/2005%E2%80%9306_Liverpool_F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19764939-1.html.csv

superlative

in the 2005 - 06 liverpool f.c. season , steven gerrard ranks the highest .

{'scope': 'all', 'col_superlative': '1', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '4', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; rank }'}, 'player'], 'result': 'steven gerrard', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; rank } ; player }'}, 'steven gerrard'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; rank } ; player } ; steven gerrard } = true', 'tointer': 'select the row whose rank record of all rows is minimum . the player record of this row is steven gerrard .'}

eq { hop { argmin { all_rows ; rank } ; player } ; steven gerrard } = true

select the row whose rank record of all rows is minimum . the player record of this row is steven gerrard .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'rank_5': 5, 'player_6': 6, 'steven gerrard_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'rank_5': 'rank', 'player_6': 'player', 'steven gerrard_7': 'steven gerrard'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'rank_5': [0], 'player_6': [1], 'steven gerrard_7': [2]}

['rank', 'no', 'pos', 'player', 'premier league', 'fa cup', 'league cup', 'champions league', 'club world cup', 'total']

[['1', '8', 'mf', 'steven gerrard', '10', '4', '1', '7', '1', '23'], ['2', '9', 'fw', 'djibril cisse', '9', '2', '0', '6', '0', '19'], ['3', '15', 'fw', 'peter crouch', '8', '3', '0', '0', '2', '13'], ['4', '10', 'mf', 'luis garcã\xada', '7', '1', '0', '2', '0', '11'], ['5', '19', 'fw', 'fernando morientes', '5', '1', '0', '3', '0', '9'], ['6', '11', 'fw', 'robbie fowler', '5', '0', '0', '0', '0', '5'], ['6', '14', 'mf', 'xabi alonso', '3', '2', '0', '0', '0', '5'], ['8', '6', 'df', 'john arne riise', '1', '3', '0', '0', '0', '4'], ['9', '7', 'mf', 'harry kewell', '3', '0', '0', '0', '0', '3'], ['9', '24', 'fw', 'florent sinama - pongolle', '0', '2', '0', '1', '0', '3'], ['11', '4', 'df', 'sami hyypia', '1', '1', '0', '0', '0', '2'], ['11', '30', 'mf', 'boudewijn zenden', '2', '0', '0', '0', '0', '2'], ['13', '23', 'df', 'jamie carragher', '0', '0', '0', '1', '0', '1'], ['13', '28', 'df', 'stephen warnock', '1', '0', '0', '0', '0', '1']]

dav \ xc3 \ xadd garza p \ xc3 \ xa9rez

https://en.wikipedia.org/wiki/Dav%C3%ADd_Garza_P%C3%A9rez

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15568742-1.html.csv

count

the placement position of 13th was held by davíd garza pérez on two occasions .

{'scope': 'all', 'criterion': 'equal', 'value': '13th', 'result': '2', 'col': '9', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'pos', '13th'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose pos record fuzzily matches to 13th .', 'tostr': 'filter_eq { all_rows ; pos ; 13th }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; pos ; 13th } }', 'tointer': 'select the rows whose pos record fuzzily matches to 13th . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; pos ; 13th } } ; 2 } = true', 'tointer': 'select the rows whose pos record fuzzily matches to 13th . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; pos ; 13th } } ; 2 } = true

select the rows whose pos record fuzzily matches to 13th . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'pos_5': 5, '13th_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'pos_5': 'pos', '13th_6': '13th', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'pos_5': [0], '13th_6': [0], '2_7': [2]}

['season', 'series', 'team', 'races', 'wins', 'poles', 'fast laps', 'points', 'pos']

[['2009', 'champ car atlantic', 'jensen motorsport', '2', '0', '0', '0', '8', '17th'], ['2008 - 09', 'a1 grand prix', 'a1 team mexico', '4', '0', '0', '0', '19', '13th ( 1 )'], ['2008', 'champ car atlantic', 'forsythe championship racing', '6', '0', '0', '0', '94', '13th'], ['2007 - 08', 'a1 grand prix', 'a1 team mexico', '10', '0', '0', '0', '5', '16th ( 1 )'], ['2007', 'champ car atlantic', 'us racetronics', '12', '0', '0', '0', '78', '17th'], ['2006', 'formula bmw usa', 'eurointernational', '14', '0', '2', '0', '42', '10th']]

indiana high school athletics conferences : mid - eastern - northwestern

https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Mid-Eastern_%E2%80%93_Northwestern

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18942405-2.html.csv

count

there are 9 schools which participated in the indiana high school athletics conference .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'school'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record is arbitrary .', 'tostr': 'filter_all { all_rows ; school }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; school } }', 'tointer': 'select the rows whose school record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; school } } ; 9 } = true', 'tointer': 'select the rows whose school record is arbitrary . the number of such rows is 9 .'}

eq { count { filter_all { all_rows ; school } } ; 9 } = true

select the rows whose school record is arbitrary . the number of such rows is 9 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'school_5': 5, '9_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'school_5': 'school', '9_6': '9'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'school_5': [0], '9_6': [2]}

['school', 'location', 'mascot', 'enrollment', 'ihsaa class', 'county']

[['edinburgh community', 'edinburgh', 'lancers', '269', 'a', '41 johnson'], ['hauser', 'hope', 'jets', '297', 'a', '03 bartholomew'], ['indian creek', 'trafalgar', 'braves', '608', 'aaa', '41 johnson'], ['morristown', 'morristown', 'yellow jackets', '231', 'a', '73 shelby'], ['north decatur', 'greensburg', 'chargers', '369', 'aa', '16 decatur'], ['south decatur', 'greensburg', 'cougars', '292', 'a', '16 decatur'], ['southwestern shelbyville', 'shelbyville', 'spartans', '218', 'a', '73 shelby'], ['triton central', 'fairland', 'tigers', '525', 'aa', '73 shelby'], ['waldron', 'waldron', 'mohawks', '237', 'a', '73 shelby']]

vern schuppan

https://en.wikipedia.org/wiki/Vern_Schuppan

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235700-2.html.csv

comparative

the only occasion where vern schuppan 's chassis was mclaren , was 1981 .

{'row_1': '4', 'row_2': '4', 'col': '1', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'yes', 'diff_result': None}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'mclaren'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren .', 'tostr': 'filter_eq { all_rows ; chassis ; mclaren }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; mclaren } ; year }', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'mclaren'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren .', 'tostr': 'filter_eq { all_rows ; chassis ; mclaren }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; chassis ; mclaren } ; year }', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; hop { filter_eq { all_rows ; chassis ; mclaren } ; year } }', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . the first record is equal to the second record .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'mclaren'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren .', 'tostr': 'filter_eq { all_rows ; chassis ; mclaren }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; chassis ; mclaren } ; year }', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row .'}, '1981'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 }', 'tointer': 'the year record of the first row is 1981 .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'chassis', 'mclaren'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren .', 'tostr': 'filter_eq { all_rows ; chassis ; mclaren }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; chassis ; mclaren } ; year }', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row .'}, '1981'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 }', 'tointer': 'the year record of the second row is 1981 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } ; eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } }', 'tointer': 'the year record of the first row is 1981 . the year record of the second row is 1981 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; hop { filter_eq { all_rows ; chassis ; mclaren } ; year } } ; and { eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } ; eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } } } = true', 'tointer': 'select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . the first record is equal to the second record . the year record of the first row is 1981 . the year record of the second row is 1981 .'}

and { eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; hop { filter_eq { all_rows ; chassis ; mclaren } ; year } } ; and { eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } ; eq { hop { filter_eq { all_rows ; chassis ; mclaren } ; year } ; 1981 } } } = true

select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . select the rows whose chassis record fuzzily matches to mclaren . take the year record of this row . the first record is equal to the second record . the year record of the first row is 1981 . the year record of the second row is 1981 .

13

9

{'and_8': 8, 'result_9': 9, 'eq_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_10': 10, 'chassis_11': 11, 'mclaren_12': 12, 'year_13': 13, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_14': 14, 'chassis_15': 15, 'mclaren_16': 16, 'year_17': 17, 'and_7': 7, 'eq_5': 5, '1981_18': 18, 'eq_6': 6, '1981_19': 19}

{'and_8': 'and', 'result_9': 'true', 'eq_4': 'eq', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_10': 'all_rows', 'chassis_11': 'chassis', 'mclaren_12': 'mclaren', 'year_13': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_14': 'all_rows', 'chassis_15': 'chassis', 'mclaren_16': 'mclaren', 'year_17': 'year', 'and_7': 'and', 'eq_5': 'eq', '1981_18': '1981', 'eq_6': 'eq', '1981_19': '1981'}

{'and_8': [9], 'result_9': [], 'eq_4': [8], 'num_hop_2': [4, 5], 'filter_str_eq_0': [2], 'all_rows_10': [0], 'chassis_11': [0], 'mclaren_12': [0], 'year_13': [2], 'num_hop_3': [4, 6], 'filter_str_eq_1': [3], 'all_rows_14': [1], 'chassis_15': [1], 'mclaren_16': [1], 'year_17': [3], 'and_7': [8], 'eq_5': [7], '1981_18': [5], 'eq_6': [7], '1981_19': [6]}

['year', 'chassis', 'engine', 'start', 'finish']

[['1976', 'eagle', 'offy', '17th', '18th'], ['1977', 'wildcat', 'offy', 'dnq', 'dnq'], ['1979', 'wildcat', 'dgs', '22nd', '21st'], ['1981', 'mclaren', 'cosworth', '18th', '3rd'], ['1982', 'penske', 'cosworth', 'dnq', 'dnq']]

law & order : special victims unit

https://en.wikipedia.org/wiki/Law_%26_Order%3A_Special_Victims_Unit

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-197060-1.html.csv

count

there were three seasons where the timeslot for law & order : special victims unit was on wednesday .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'wednesday', 'result': '3', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'timeslot ( est )', 'wednesday'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose timeslot ( est ) record fuzzily matches to wednesday .', 'tostr': 'filter_eq { all_rows ; timeslot ( est ) ; wednesday }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; timeslot ( est ) ; wednesday } }', 'tointer': 'select the rows whose timeslot ( est ) record fuzzily matches to wednesday . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; timeslot ( est ) ; wednesday } } ; 3 } = true', 'tointer': 'select the rows whose timeslot ( est ) record fuzzily matches to wednesday . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; timeslot ( est ) ; wednesday } } ; 3 } = true

select the rows whose timeslot ( est ) record fuzzily matches to wednesday . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'timeslot (est)_5': 5, 'Wednesday_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'timeslot (est)_5': 'timeslot ( est )', 'Wednesday_6': 'wednesday', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'timeslot (est)_5': [0], 'Wednesday_6': [0], '3_7': [2]}

['season', 'episodes', 'timeslot ( est )', 'season premiere', 'season finale', 'tv season', 'ranking', 'viewers ( in millions )']

[['1', '22', 'monday 9:00 pm ( 1999 ) friday 10:00 pm ( 2000 )', 'september 20 , 1999', 'may 19 , 2000', '1999 - 2000', '33rd', '12.18'], ['2', '21', 'friday 10:00 pm', 'october 20 , 2000', 'may 11 , 2001', '2000 - 01', '29th', '13.1'], ['3', '23', 'friday 10:00 pm', 'september 28 , 2001', 'may 17 , 2002', '2001 - 02', '14th', '15.2'], ['4', '25', 'friday 10:00 pm', 'september 27 , 2002', 'may 16 , 2003', '2002 - 03', '16th', '14.83'], ['5', '25', 'tuesday 10:00 pm', 'september 23 , 2003', 'may 18 , 2004', '2003 - 04', '21st', '12.72'], ['6', '23', 'tuesday 10:00 pm', 'september 21 , 2004', 'may 24 , 2005', '2004 - 05', '23rd', '13.46'], ['7', '22', 'tuesday 10:00 pm', 'september 20 , 2005', 'may 16 , 2006', '2005 - 06', '24th', '13.78'], ['8', '22', 'tuesday 10:00 pm', 'september 19 , 2006', 'may 22 , 2007', '2006 - 07', '38th', '11.94'], ['9', '19', 'tuesday 10:00 pm', 'september 25 , 2007', 'may 13 , 2008', '2007 - 08', '30th', '11.33'], ['10', '22', 'tuesday 10:00 pm', 'september 23 , 2008', 'june 2 , 2009', '2008 - 09', '39th', '10.11'], ['11', '24', 'wednesday 9:00 pm wednesday 10:00 pm', 'september 23 , 2009', 'may 19 , 2010', '2009 - 10', '44th', '8.81'], ['13', '23', 'wednesday 10:00 pm', 'september 21 , 2011', 'may 23 , 2012', '2011 - 12', '67th', '7.59'], ['14', '24', 'wednesday 9:00 pm', 'september 26 , 2012', 'may 22 , 2013', '2012 - 13', '56th', '7.30']]

outback ( region )

https://en.wikipedia.org/wiki/Outback_%28region%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23685890-2.html.csv

comparative

anangu pitjantjatjara yankunytjatjara had a smaller population in 2006 than the outback areas community development trust .

{'row_1': '3', 'row_2': '7', 'col': '5', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'local government area', 'anangu pitjantjatjara yankunytjatjara'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose local government area record fuzzily matches to anangu pitjantjatjara yankunytjatjara .', 'tostr': 'filter_eq { all_rows ; local government area ; anangu pitjantjatjara yankunytjatjara }'}, 'pop 2006'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; local government area ; anangu pitjantjatjara yankunytjatjara } ; pop 2006 }', 'tointer': 'select the rows whose local government area record fuzzily matches to anangu pitjantjatjara yankunytjatjara . take the pop 2006 record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'local government area', 'outback areas community development trust'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose local government area record fuzzily matches to outback areas community development trust .', 'tostr': 'filter_eq { all_rows ; local government area ; outback areas community development trust }'}, 'pop 2006'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; local government area ; outback areas community development trust } ; pop 2006 }', 'tointer': 'select the rows whose local government area record fuzzily matches to outback areas community development trust . take the pop 2006 record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; local government area ; anangu pitjantjatjara yankunytjatjara } ; pop 2006 } ; hop { filter_eq { all_rows ; local government area ; outback areas community development trust } ; pop 2006 } } = true', 'tointer': 'select the rows whose local government area record fuzzily matches to anangu pitjantjatjara yankunytjatjara . take the pop 2006 record of this row . select the rows whose local government area record fuzzily matches to outback areas community development trust . take the pop 2006 record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; local government area ; anangu pitjantjatjara yankunytjatjara } ; pop 2006 } ; hop { filter_eq { all_rows ; local government area ; outback areas community development trust } ; pop 2006 } } = true

select the rows whose local government area record fuzzily matches to anangu pitjantjatjara yankunytjatjara . take the pop 2006 record of this row . select the rows whose local government area record fuzzily matches to outback areas community development trust . take the pop 2006 record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'local government area_7': 7, 'anangu pitjantjatjara yankunytjatjara_8': 8, 'pop 2006_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'local government area_11': 11, 'outback areas community development trust_12': 12, 'pop 2006_13': 13}

{'less_4': 'less', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'local government area_7': 'local government area', 'anangu pitjantjatjara yankunytjatjara_8': 'anangu pitjantjatjara yankunytjatjara', 'pop 2006_9': 'pop 2006', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'local government area_11': 'local government area', 'outback areas community development trust_12': 'outback areas community development trust', 'pop 2006_13': 'pop 2006'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'local government area_7': [0], 'anangu pitjantjatjara yankunytjatjara_8': [0], 'pop 2006_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'local government area_11': [1], 'outback areas community development trust_12': [1], 'pop 2006_13': [3]}

['local government area', 'type', 'major town', 'land area ( km square )', 'pop 2006', 'density km 2', 'towns', 'est']

[['roxby downs', 'municipal council', 'roxby downs', '110', '4292', '39018', '2', '1982'], ['coober pedy', 'district council', 'coober pedy', '77 , 8', '1996', '25656', '1', '1987'], ['anangu pitjantjatjara yankunytjatjara', 'aboriginal council', 'umuwa', '102650', '2204', '21', '18', '1981'], ['maralinga tjarutja 1 )', 'aboriginal council', 'oak valley', '102863 , 6', '105', '1', '1', '1984'], ['yalata', 'aboriginal council', 'yalata', '4563', '100', '22', '1', '1994'], ['nepabunna', 'aboriginal council', 'nepabunna , south australia', '76 , 4', '49', '641', '1', '1998'], ['outback areas community development trust', 'unincorporated area', 'leigh creek', '624339.0', '3750', '6', '36', '1978']]

1940 world series

https://en.wikipedia.org/wiki/1940_World_Series

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1332360-1.html.csv

superlative

the detroit tigers scored the most runs of all their games , in game 5 .

{'scope': 'all', 'col_superlative': '3', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'game'], 'result': '5', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; game }'}, '5'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; game } ; 5 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the game record of this row is 5 .'}

eq { hop { argmax { all_rows ; score } ; game } ; 5 } = true

select the row whose score record of all rows is maximum . the game record of this row is 5 .

3

3

{'eq_2': 2, 'result_3': 3, 'num_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'game_6': 6, '5_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'num_hop_1': 'num_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'game_6': 'game', '5_7': '5'}

{'eq_2': [3], 'result_3': [], 'num_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'game_6': [1], '5_7': [2]}

['game', 'date', 'score', 'location', 'time', 'attendance']

[['1', 'october 2', 'detroit tigers - 7 , cincinnati reds - 2', 'crosley field', '2:09', '31793'], ['2', 'october 3', 'detroit tigers - 3 , cincinnati reds - 5', 'crosley field', '1:54', '30640'], ['3', 'october 4', 'cincinnati reds - 4 , detroit tigers - 7', 'briggs stadium', '2:08', '52877'], ['4', 'october 5', 'cincinnati reds - 5 , detroit tigers - 2', 'briggs stadium', '2:06', '54093'], ['5', 'october 6', 'cincinnati reds - 0 , detroit tigers - 8', 'briggs stadium', '2:26', '55189'], ['6', 'october 7', 'detroit tigers - 0 , cincinnati reds - 4', 'crosley field', '2:01', '30481'], ['7', 'october 8', 'detroit tigers - 1 , cincinnati reds - 2', 'crosley field', '1:47', '26854']]

volleyball at the 2004 summer olympics - men 's team rosters

https://en.wikipedia.org/wiki/Volleyball_at_the_2004_Summer_Olympics_%E2%80%93_Men%27s_team_rosters

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15859432-12.html.csv

aggregation

the average weight for the men 's volleyball team at the 2004 summer olympics is 95.5 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '95.5', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'weight'], 'result': '95.5', 'ind': 0, 'tostr': 'avg { all_rows ; weight }'}, '95.5'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; weight } ; 95.5 } = true', 'tointer': 'the average of the weight record of all rows is 95.5 .'}

round_eq { avg { all_rows ; weight } ; 95.5 } = true

the average of the weight record of all rows is 95.5 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'weight_4': 4, '95.5_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'weight_4': 'weight', '95.5_5': '95.5'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'weight_4': [0], '95.5_5': [1]}

['name', 'date of birth', 'height', 'weight', 'spike', 'block']

[['lloy ball', '17.02.1972', '203', '95', '351', '316'], ['erik sullivan', '09.08.1972', '193', '86', '340', '320'], ['phillip eatherton', '02.01.1974', '206', '101', '356', '335'], ['donald suxho', '21.02.1976', '196', '98', '337', '319'], ['william priddy', '01.10.1977', '196', '89', '353', '330'], ['ryan millar', '22.01.1978', '204', '98', '354', '326'], ['riley salmon', '02.07.1976', '197', '89', '345', '331'], ['brook billings', '30.04.1980', '196', '95', '351', '331'], ['thomas hoff', '09.06.1973', '198', '94', '353', '333'], ['clayton stanley', '20.01.1978', '205', '104', '357', '332'], ['kevin barnett', '14.05.1974', '198', '94', '353', '340'], ['gabriel gardner', '18.03.1976', '209', '103', '353', '335']]

moussa mazou

https://en.wikipedia.org/wiki/Moussa_Ma%C3%A2zou

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18707391-1.html.csv

superlative

the niger national team scored the most goals with mazou scoring at least one ( 4 ) against liberia on 9 october 2012 .

{'scope': 'all', 'col_superlative': '3', 'row_superlative': '6', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; score }'}, 'date'], 'result': '9 october 2012', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; score } ; date }'}, '9 october 2012'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; score } ; date } ; 9 october 2012 } = true', 'tointer': 'select the row whose score record of all rows is maximum . the date record of this row is 9 october 2012 .'}

eq { hop { argmax { all_rows ; score } ; date } ; 9 october 2012 } = true

select the row whose score record of all rows is maximum . the date record of this row is 9 october 2012 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'score_5': 5, 'date_6': 6, '9 october 2012_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'score_5': 'score', 'date_6': 'date', '9 october 2012_7': '9 october 2012'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'score_5': [0], 'date_6': [1], '9 october 2012_7': [2]}

['date', 'venue', 'score', 'result', 'competition']

[['10 october 2010', 'stade général seyni kountché , niamey', '1 - 0', '1 - 0', '2012 africa cup of nations qualifier'], ['17 november 2010', 'june 11 stadium , tripoli', '1 - 1', '1 - 1', 'friendly'], ['10 august 2011', 'stade général seyni kountché , niamey', '1 - 2', '3 - 3', 'friendly'], ['10 august 2011', 'stade général seyni kountché , niamey', '2 - 3', '3 - 3', 'friendly'], ['4 september 2011', 'stade général seyni kountché , niamey', '2 - 0', '2 - 1', '2012 africa cup of nations qualifier'], ['9 october 2012', 'stade général seyni kountché , niamey', '4 - 3', '4 - 3', 'friendly']]

axis & allies

https://en.wikipedia.org/wiki/Axis_%26_Allies

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-173475-1.html.csv

aggregation

the average number of pieces that axis & allies had was 271.6 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '271.6', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'pieces'], 'result': '271.6', 'ind': 0, 'tostr': 'avg { all_rows ; pieces }'}, '271.6'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; pieces } ; 271.6 } = true', 'tointer': 'the average of the pieces record of all rows is 271.6 .'}

round_eq { avg { all_rows ; pieces } ; 271.6 } = true

the average of the pieces record of all rows is 271.6 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'pieces_4': 4, '271.6_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'pieces_4': 'pieces', '271.6_5': '271.6'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'pieces_4': [0], '271.6_5': [1]}

['release', 'title', 'start', 'pieces', 'board ( inches )', 'board ( cm )', 'type', 'new units new units when compared to the original a & a : classic version of the game', 'playable powers']

[['1981', 'axis & allies ( nova games edition )', '1942', '415', '37 19 ½', '93 50', 'global', 'same as classic plus nuke pieces were cardboard', '5 : germany , japan , ussr , uk , usa'], ['1999', 'axis & allies : europe', '1941', '373', '30 20', '75 50', 'theater', 'destroyer , artillery', '4 : germany , ussr , uk , usa'], ['2004', 'axis & allies : d - day', '1944', '241', '30 20', '75 50', 'local', 'artillery , blockhouse', '3 : germany , uk , usa'], ['2006', 'axis & allies : battle of the bulge', '1944', '157', '30 20', '75 50', 'local', 'artillery , truck', '3 : germany , uk , usa'], ['2007', 'axis & allies : guadalcanal', '1942', '172', '30 20', '75 50', 'local', 'destroyer , cruiser , artillery', '2 : japan , usa']]

fiba eurobasket 2007 squads

https://en.wikipedia.org/wiki/FIBA_EuroBasket_2007_squads

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-12962773-15.html.csv

count

a total of three players on the fiba eurobasket 2007 squad play the forward position .

{'scope': 'all', 'criterion': 'equal', 'value': 'forward', 'result': '3', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'forward'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to forward .', 'tostr': 'filter_eq { all_rows ; position ; forward }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; position ; forward } }', 'tointer': 'select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; position ; forward } } ; 3 } = true', 'tointer': 'select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; position ; forward } } ; 3 } = true

select the rows whose position record fuzzily matches to forward . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, 'forward_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', 'forward_6': 'forward', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], 'forward_6': [0], '3_7': [2]}

['no', 'player', 'height', 'position', 'year born', 'current club']

[['4', 'marco belinelli', '1.96', 'guard', '1986', 'golden state warriors'], ['5', 'gianluca basile', '1.95', 'guard', '1975', 'axa fc barcelona'], ['6', 'stefano mancinelli', '2.03', 'forward', '1983', 'climamio bologna'], ['7', 'matteo soragna', '1.97', 'guard', '1975', 'benetton treviso'], ['8', 'denis marconato', '2.12', 'center', '1975', 'axa fc barcelona'], ['9', 'marco mordente', '1.90', 'guard', '1979', 'benetton treviso'], ['10', 'andrea bargnani', '2.12', 'forward', '1985', 'toronto raptors'], ['11', 'andrea crosariol', '2.13', 'center', '1984', 'vidivici bologna'], ['12', 'massimo bulleri', '1.87', 'guard', '1977', 'armani jeans milano'], ['13', 'fabio di bella', '1.86', 'guard', '1978', 'vidivici bologna'], ['14', 'luigi datome', '2.02', 'forward', '1987', 'legea scafati']]

1970 vfl season

https://en.wikipedia.org/wiki/1970_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1164217-10.html.csv

majority

all of the games took place on june 6 , 1970 .

{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'equal', 'value': '6 june 1970', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'date', '6 june 1970'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 6 june 1970 .', 'tostr': 'all_eq { all_rows ; date ; 6 june 1970 } = true'}

all_eq { all_rows ; date ; 6 june 1970 } = true

for the date records of all rows , all of them fuzzily match to 6 june 1970 .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '6 june 1970_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '6 june 1970_4': '6 june 1970'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '6 june 1970_4': [0]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['fitzroy', '14.9 ( 93 )', 'south melbourne', '12.19 ( 91 )', 'junction oval', '16971', '6 june 1970'], ['essendon', '14.13 ( 97 )', 'richmond', '15.14 ( 104 )', 'windy hill', '20650', '6 june 1970'], ['collingwood', '14.23 ( 107 )', 'st kilda', '15.10 ( 100 )', 'victoria park', '30858', '6 june 1970'], ['melbourne', '10.14 ( 74 )', 'geelong', '13.13 ( 91 )', 'mcg', '27665', '6 june 1970'], ['footscray', '15.14 ( 104 )', 'carlton', '14.10 ( 94 )', 'western oval', '22262', '6 june 1970'], ['north melbourne', '9.8 ( 62 )', 'hawthorn', '11.9 ( 75 )', 'vfl park', '14214', '6 june 1970']]

1941 vfl season

https://en.wikipedia.org/wiki/1941_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-11.html.csv

majority

in the 1941 vfl season , when the home team 's score is over 10 , for most games the crowd was under 20000 .

{'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'less_than', 'value': '20000', 'subset': {'col': '2', 'criterion': 'greater_than', 'value': '10'}}

{'func': 'most_less', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'home team score', '10'], 'result': None, 'ind': 0, 'tostr': 'filter_greater { all_rows ; home team score ; 10 }', 'tointer': 'select the rows whose home team score record is greater than 10 .'}, 'crowd', '20000'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose home team score record is greater than 10 . for the crowd records of these rows , most of them are less than 20000 .', 'tostr': 'most_less { filter_greater { all_rows ; home team score ; 10 } ; crowd ; 20000 } = true'}

most_less { filter_greater { all_rows ; home team score ; 10 } ; crowd ; 20000 } = true

select the rows whose home team score record is greater than 10 . for the crowd records of these rows , most of them are less than 20000 .

2

2

{'most_less_1': 1, 'result_2': 2, 'filter_greater_0': 0, 'all_rows_3': 3, 'home team score_4': 4, '10_5': 5, 'crowd_6': 6, '20000_7': 7}

{'most_less_1': 'most_less', 'result_2': 'true', 'filter_greater_0': 'filter_greater', 'all_rows_3': 'all_rows', 'home team score_4': 'home team score', '10_5': '10', 'crowd_6': 'crowd', '20000_7': '20000'}

{'most_less_1': [2], 'result_2': [], 'filter_greater_0': [1], 'all_rows_3': [0], 'home team score_4': [0], '10_5': [0], 'crowd_6': [1], '20000_7': [1]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['melbourne', '14.24 ( 108 )', 'richmond', '8.13 ( 61 )', 'mcg', '21000', '12 july 1941'], ['hawthorn', '13.12 ( 90 )', 'st kilda', '9.15 ( 69 )', 'glenferrie oval', '4000', '12 july 1941'], ['fitzroy', '18.15 ( 123 )', 'north melbourne', '18.16 ( 124 )', 'brunswick street oval', '8000', '12 july 1941'], ['essendon', '15.14 ( 104 )', 'footscray', '9.11 ( 65 )', 'windy hill', '15000', '12 july 1941'], ['geelong', '7.16 ( 58 )', 'collingwood', '14.12 ( 96 )', 'kardinia park', '7500', '12 july 1941'], ['south melbourne', '16.13 ( 109 )', 'carlton', '14.9 ( 93 )', 'lake oval', '14000', '12 july 1941']]

list of radio stations in tamaulipas

https://en.wikipedia.org/wiki/List_of_radio_stations_in_Tamaulipas

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17982829-9.html.csv

ordinal

the radio station in tamaulipas with the callsign xeas broadcasts on the third highest frequency .

{'row': '9', 'col': '1', 'order': '3', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'frequency', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; frequency ; 3 }'}, 'callsign'], 'result': 'xeas', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; frequency ; 3 } ; callsign }'}, 'xeas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; frequency ; 3 } ; callsign } ; xeas } = true', 'tointer': 'select the row whose frequency record of all rows is 3rd maximum . the callsign record of this row is xeas .'}

eq { hop { nth_argmax { all_rows ; frequency ; 3 } ; callsign } ; xeas } = true

select the row whose frequency record of all rows is 3rd maximum . the callsign record of this row is xeas .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'frequency_5': 5, '3_6': 6, 'callsign_7': 7, 'xeas_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'frequency_5': 'frequency', '3_6': '3', 'callsign_7': 'callsign', 'xeas_8': 'xeas'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'frequency_5': [0], '3_6': [0], 'callsign_7': [1], 'xeas_8': [2]}

['frequency', 'power d / n', 'callsign', 'brand', 'city of license']

[['790', '1 kw / 500w', 'xefe', 'la pura ley', 'nuevo laredo'], ['890', '10 / 1 kw', 'kvoz', 'la radio cristiana ( kczo )', 'laredo'], ['960', '5 / 1 kw', 'xek', 'la estación grande', 'nuevo laredo'], ['1000', '1 kw / 250w', 'xenlt', 'radio formula', 'nuevo laredo'], ['1090', '1 kw / 250w', 'xewl', 'w radio ( xew )', 'nuevo laredo'], ['1300', '1 kw / 500w', 'klar', 'radio poder', 'laredo'], ['1340', '1 / 1 kw', 'xebk', 'el norteñazo', 'nuevo laredo'], ['1370', '1 kw / 250w', 'xegnk', 'mariachi estéreo', 'nuevo laredo'], ['1410', '1 kw / 250w', 'xeas', 'ke buena xhpo', 'nuevo laredo'], ['1490', '1 / 1 kw', 'klnt', 'espn radio', 'laredo'], ['1550', '5 kw / 250w', 'xenu', 'la rancherita', 'nuevo laredo']]

cultural interest fraternities and sororities

https://en.wikipedia.org/wiki/Cultural_interest_fraternities_and_sororities

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2538117-12.html.csv

unique

only delta epsilon sigma iota was founded at the university of buffalo , suny .

{'scope': 'all', 'row': '8', 'col': '5', 'col_other': '2', 'criterion': 'equal', 'value': 'university at buffalo , suny', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'founding university', 'university at buffalo , suny'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founding university record fuzzily matches to university at buffalo , suny .', 'tostr': 'filter_eq { all_rows ; founding university ; university at buffalo , suny }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; founding university ; university at buffalo , suny } }', 'tointer': 'select the rows whose founding university record fuzzily matches to university at buffalo , suny . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'founding university', 'university at buffalo , suny'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose founding university record fuzzily matches to university at buffalo , suny .', 'tostr': 'filter_eq { all_rows ; founding university ; university at buffalo , suny }'}, 'organization'], 'result': 'delta epsilon sigma iota', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; founding university ; university at buffalo , suny } ; organization }'}, 'delta epsilon sigma iota'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; founding university ; university at buffalo , suny } ; organization } ; delta epsilon sigma iota }', 'tointer': 'the organization record of this unqiue row is delta epsilon sigma iota .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; founding university ; university at buffalo , suny } } ; eq { hop { filter_eq { all_rows ; founding university ; university at buffalo , suny } ; organization } ; delta epsilon sigma iota } } = true', 'tointer': 'select the rows whose founding university record fuzzily matches to university at buffalo , suny . there is only one such row in the table . the organization record of this unqiue row is delta epsilon sigma iota .'}

and { only { filter_eq { all_rows ; founding university ; university at buffalo , suny } } ; eq { hop { filter_eq { all_rows ; founding university ; university at buffalo , suny } ; organization } ; delta epsilon sigma iota } } = true

select the rows whose founding university record fuzzily matches to university at buffalo , suny . there is only one such row in the table . the organization record of this unqiue row is delta epsilon sigma iota .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'founding university_7': 7, 'university at buffalo , suny_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'organization_9': 9, 'delta epsilon sigma iota_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'founding university_7': 'founding university', 'university at buffalo , suny_8': 'university at buffalo , suny', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'organization_9': 'organization', 'delta epsilon sigma iota_10': 'delta epsilon sigma iota'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'founding university_7': [0], 'university at buffalo , suny_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'organization_9': [2], 'delta epsilon sigma iota_10': [3]}

['letters', 'organization', 'nickname', 'founding date', 'founding university', 'type']

[['αιο', 'alpha iota omicron', 'aio', '1998 - 10 - 16', 'university of michigan', 'fraternity'], ['βχθ', 'beta chi theta 2', 'beta chi / bct', '1999 - 06 - 02', 'university of california , los angeles', 'fraternity'], ['βκγ', 'beta kappa gamma', 'bkg', '1999 - 05 - 06', 'university of texas at austin', 'fraternity'], ['δσι', 'delta sigma iota', 'dsi', '2000 - 08 - 15', 'pennsylvania state university', 'fraternity'], ['δεψ', 'delta epsilon psi', 'depsi / depsi', '1998 - 10 - 01', 'university of texas at austin', 'fraternity'], ['δθψ', 'delta theta psi', 'dtpsi', '2002 - 01 - 14', 'university of michigan', 'sorority'], ['δκδ', 'delta kappa delta 1', 'dkd', '2000 - 08 - 15', 'texas a & m university', 'sorority'], ['δeσι', 'delta epsilon sigma iota', 'desi', '1997 - 12 - 12', 'university at buffalo , suny', 'fraternity'], ['δφω', 'delta phi omega', 'dpo', '1998 - 12 - 06', 'university of houston', 'sorority'], ['ινδ', 'iota nu delta', 'ind', '1994 - 02 - 07', 'binghamton university', 'fraternity'], ['κφγ', 'kappa phi gamma', 'kphig', '1998 - 11 - 08', 'university of texas at austin', 'sorority']]

2012 in film

https://en.wikipedia.org/wiki/2012_in_film

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16921964-1.html.csv

ordinal

the hobbit : an unexpected journey had the 4th largest wordwide gross of 2012 films .

{'row': '4', 'col': '5', 'order': '4', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'worldwide gross', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; worldwide gross ; 4 }'}, 'title'], 'result': 'the hobbit : an unexpected journey', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; worldwide gross ; 4 } ; title }'}, 'the hobbit : an unexpected journey'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; worldwide gross ; 4 } ; title } ; the hobbit : an unexpected journey } = true', 'tointer': 'select the row whose worldwide gross record of all rows is 4th maximum . the title record of this row is the hobbit : an unexpected journey .'}

eq { hop { nth_argmax { all_rows ; worldwide gross ; 4 } ; title } ; the hobbit : an unexpected journey } = true

select the row whose worldwide gross record of all rows is 4th maximum . the title record of this row is the hobbit : an unexpected journey .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'worldwide gross_5': 5, '4_6': 6, 'title_7': 7, 'the hobbit : an unexpected journey_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'worldwide gross_5': 'worldwide gross', '4_6': '4', 'title_7': 'title', 'the hobbit : an unexpected journey_8': 'the hobbit : an unexpected journey'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'worldwide gross_5': [0], '4_6': [0], 'title_7': [1], 'the hobbit : an unexpected journey_8': [2]}

['rank', 'title', 'studio', 'director ( s )', 'worldwide gross']

[['1', 'the avengers', 'marvel / disney', 'joss whedon', '1511757910'], ['2', 'skyfall', 'mgm / columbia pictures', 'sam mendes', '1108561013'], ['3', 'the dark knight rises', 'warner bros / legendary pictures', 'christopher nolan', '1084439099'], ['4', 'the hobbit : an unexpected journey', 'warner bros / mgm / new line', 'peter jackson', '1017003568'], ['5', 'ice age : continental drift', '20th century fox / blue sky', 'steve martino and mike thurmeier', '877244782'], ['6', 'the twilight saga : breaking dawn - part 2', 'lionsgate / summit', 'bill condon', '829224737'], ['7', 'the amazing spider - man', 'columbia pictures', 'marc webb', '752216557'], ['8', "madagascar 3 : europe 's most wanted", 'paramount / dreamworks', 'eric darnell , tom mcgrath and conrad vernon', '746921274'], ['9', 'the hunger games', 'lionsgate', 'gary ross', '691247768'], ['10', 'men in black 3', 'columbia pictures', 'barry sonnenfeld', '624026776'], ['11', 'life of pi', '20th century fox', 'ang lee', '609016565'], ['12', 'ted', 'universal pictures', 'seth macfarlane', '549368315'], ['13', 'brave', 'walt disney pictures / pixar animation studios', 'mark andrews and brenda chapman', '538983207'], ['14', 'wreck - it ralph', 'walt disney pictures', 'rich moore', '471222889'], ['15', 'les misérables', 'universal pictures', 'tom hooper', '441809770'], ['16', 'the intouchables', 'gaumont film company', 'olivier nakache and éric toledano', '426588510'], ['17', 'django unchained', 'the weinstein company / columbia pictures', 'quentin tarantino', '425368238'], ['18', 'prometheus', '20th century fox', 'ridley scott', '403354469'], ['19', 'snow white and the huntsman', 'universal pictures', 'rupert sanders', '396592829'], ['20', 'taken 2', '20th century fox', 'olivier megaton', '376141306']]

list of england national rugby union team results 1990 - 99

https://en.wikipedia.org/wiki/List_of_England_national_rugby_union_team_results_1990%E2%80%9399

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18178534-3.html.csv

count

two of the statuses were a test match .

{'scope': 'all', 'criterion': 'equal', 'value': 'test match', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'status', 'test match'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose status record fuzzily matches to test match .', 'tostr': 'filter_eq { all_rows ; status ; test match }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; status ; test match } }', 'tointer': 'select the rows whose status record fuzzily matches to test match . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; status ; test match } } ; 2 } = true', 'tointer': 'select the rows whose status record fuzzily matches to test match . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; status ; test match } } ; 2 } = true

select the rows whose status record fuzzily matches to test match . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'status_5': 5, 'test match_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'status_5': 'status', 'test match_6': 'test match', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'status_5': [0], 'test match_6': [0], '2_7': [2]}

['opposing teams', 'against', 'date', 'venue', 'status']

[['scotland', '7', '18 / 01 / 1992', 'murrayfield , edinburgh', 'five nations'], ['ireland', '9', '01 / 02 / 1992', 'twickenham , london', 'five nations'], ['france', '13', '15 / 02 / 1992', 'parc des princes , paris', 'five nations'], ['wales', '0', '07 / 03 / 1992', 'twickenham , london', 'five nations'], ['canada', '13', '17 / 10 / 1992', 'wembley stadium , london', 'test match'], ['south africa', '16', '14 / 11 / 1992', 'twickenham , london', 'test match']]

1980 world judo championships

https://en.wikipedia.org/wiki/1980_World_Judo_Championships

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15826103-2.html.csv

count

9 nations were represented in the world judo championships of 1980 .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'rank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose rank record is arbitrary .', 'tostr': 'filter_all { all_rows ; rank }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; rank } }', 'tointer': 'select the rows whose rank record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; rank } } ; 9 } = true', 'tointer': 'select the rows whose rank record is arbitrary . the number of such rows is 9 .'}

eq { count { filter_all { all_rows ; rank } } ; 9 } = true

select the rows whose rank record is arbitrary . the number of such rows is 9 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'rank_5': 5, '9_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'rank_5': 'rank', '9_6': '9'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'rank_5': [0], '9_6': [2]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'austria', '3', '0', '0', '3'], ['2', 'france', '1', '3', '4', '8'], ['3', 'italy', '1', '2', '0', '3'], ['4', 'great britain', '1', '1', '3', '5'], ['5', 'belgium', '1', '0', '2', '3'], ['6', 'netherlands', '1', '0', '1', '2'], ['7', 'germany', '0', '1', '3', '4'], ['8', 'japan', '0', '1', '0', '1'], ['9', 'united states', '0', '0', '3', '3']]

list of childrens hospital episodes

https://en.wikipedia.org/wiki/List_of_Childrens_Hospital_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28081876-4.html.csv

comparative

the childrens hospital episode titled " joke overload " had an original air date that was 7 days before the original air date for the episode titled " end of the middle . " .

{'row_1': '5', 'row_2': '6', 'col': '6', 'col_other': '3', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '7', 'bigger': 'row2'}}

{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'joke overload'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to joke overload .', 'tostr': 'filter_eq { all_rows ; title ; joke overload }'}, 'original air date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; joke overload } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to joke overload . take the original air date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'end of the middle'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to end of the middle .', 'tostr': 'filter_eq { all_rows ; title ; end of the middle }'}, 'original air date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; end of the middle } ; original air date }', 'tointer': 'select the rows whose title record fuzzily matches to end of the middle . take the original air date record of this row .'}], 'result': '-7', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; title ; joke overload } ; original air date } ; hop { filter_eq { all_rows ; title ; end of the middle } ; original air date } }'}, '-7'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; title ; joke overload } ; original air date } ; hop { filter_eq { all_rows ; title ; end of the middle } ; original air date } } ; -7 } = true', 'tointer': 'select the rows whose title record fuzzily matches to joke overload . take the original air date record of this row . select the rows whose title record fuzzily matches to end of the middle . take the original air date record of this row . the second record is 7 larger than the first record .'}

eq { diff { hop { filter_eq { all_rows ; title ; joke overload } ; original air date } ; hop { filter_eq { all_rows ; title ; end of the middle } ; original air date } } ; -7 } = true

select the rows whose title record fuzzily matches to joke overload . take the original air date record of this row . select the rows whose title record fuzzily matches to end of the middle . take the original air date record of this row . the second record is 7 larger than the first record .

6

6

{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'title_8': 8, 'joke overload_9': 9, 'original air date_10': 10, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'title_12': 12, 'end of the middle_13': 13, 'original air date_14': 14, '-7_15': 15}

{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'title_8': 'title', 'joke overload_9': 'joke overload', 'original air date_10': 'original air date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'title_12': 'title', 'end of the middle_13': 'end of the middle', 'original air date_14': 'original air date', '-7_15': '-7'}

{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'title_8': [0], 'joke overload_9': [0], 'original air date_10': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'title_12': [1], 'end of the middle_13': [1], 'original air date_14': [3], '-7_15': [5]}

['series no', 'season no', 'title', 'directed by', 'written by', 'original air date', 'production code']

[['6', '1', 'i see her face everywhere', 'matt shakman', 'rob corddry', 'august 22 , 2010', '201'], ['7', '2', 'no one can replace her', 'matt shakman', 'rob corddry', 'august 29 , 2010', '202'], ['8', '3', 'i am not afraid of any ghost', 'bryan gordon', 'rob huebel', 'september 5 , 2010', '203'], ['9', '4', 'give a painted brother a break', 'rob schrab', 'paul scheer', 'september 12 , 2010', '205'], ['10', '5', 'joke overload', 'john inwood', 'jason mantzoukas', 'september 19 , 2010', '207'], ['11', '6', 'end of the middle', 'david wain', 'jonathan stern', 'september 26 , 2010', '206'], ['13', '8', 'hot enough for you', 'david wain', 'rob corddry & david wain', 'october 10 , 2010', '208'], ['14', '9', 'the coffee machine paid for itself', 'bryan gordon', 'ken marino & erica oyama', 'october 17 , 2010', '209'], ['16', '11', 'you know no one can hear you , right', 'ken marino', 'brian huskey and rob corddry', 'october 31 , 2010', '211']]

united states house of representatives elections , 1994

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1994

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341522-36.html.csv

majority

most of the incumbents of the 1994 united states house of representatives elections were from the democratic party .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'democratic', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'party', 'democratic'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to democratic .', 'tostr': 'most_eq { all_rows ; party ; democratic } = true'}

most_eq { all_rows ; party ; democratic } = true

for the party records of all rows , most of them fuzzily match to democratic .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'democratic_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'democratic_4': 'democratic'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'democratic_4': [0]}

['district', 'incumbent', 'party', 'first elected', 'status', 'opponent']

[['north carolina1', 'eva m clayton', 'democratic', '1992', 're - elected', 'eva m clayton ( d ) 61.1 % ted tyler ( r ) 38.9 %'], ['north carolina4', 'david price', 'democratic', '1986', 'defeated republican gain', 'fred heineman ( r ) 50.4 % david price ( d ) 49.6 %'], ['north carolina5', 'stephen l neal', 'democratic', '1974', 'retired republican gain', 'richard burr ( r ) 57.3 % a p sands ( d ) 42.7 %'], ['north carolina6', 'howard coble', 'republican', '1984', 're - elected', 'howard coble ( r ) unopposed'], ['north carolina8', 'bill hefner', 'democratic', '1974', 're - elected', 'bill hefner ( d ) 52.4 % sherrill morgan ( r ) 47.6 %'], ['north carolina9', 'alex mcmillan', 'republican', '1984', 'retired republican hold', 'sue wilkins myrick ( r ) 65.0 % rory blake ( d ) 35.0 %']]

1953 los angeles rams season

https://en.wikipedia.org/wiki/1953_Los_Angeles_Rams_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11172588-1.html.csv

majority

the rams won a majority of games during their 1953 season .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'w', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'w'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to w .', 'tostr': 'most_eq { all_rows ; result ; w } = true'}

most_eq { all_rows ; result ; w } = true

for the result records of all rows , most of them fuzzily match to w .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'w_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'w_4': 'w'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'w_4': [0]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 27 , 1953', 'new york giants', 'w 21 - 7', '49579'], ['2', 'october 4 , 1953', 'san francisco 49ers', 'l 31 - 30', '43922'], ['3', 'october 11 , 1953', 'green bay packers', 'w 38 - 20', '23353'], ['4', 'october 18 , 1953', 'detroit lions', 'w 31 - 19', '55772'], ['5', 'october 25 , 1953', 'chicago bears', 'w 38 - 24', '49546'], ['6', 'november 1 , 1953', 'detroit lions', 'w 37 - 24', '93751'], ['7', 'november 8 , 1953', 'san francisco 49ers', 'l 31 - 27', '85865'], ['8', 'november 15 , 1953', 'chicago cardinals', 't 24 - 24', '26674'], ['9', 'november 22 , 1953', 'baltimore colts', 'w 21 - 13', '27268'], ['10', 'november 29 , 1953', 'chicago bears', 'l 24 - 21', '31626'], ['11', 'december 5 , 1953', 'baltimore colts', 'w 45 - 2', '26656'], ['12', 'december 12 , 1953', 'green bay packers', 'w 33 - 17', '23069']]

united states house of representatives elections , 1984

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1984

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1341598-36.html.csv

majority

most of the incumbents of the 1984 house of representatives elections were from the republican party .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'republican', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'party', 'republican'], 'result': True, 'ind': 0, 'tointer': 'for the party records of all rows , most of them fuzzily match to republican .', 'tostr': 'most_eq { all_rows ; party ; republican } = true'}

most_eq { all_rows ; party ; republican } = true

for the party records of all rows , most of them fuzzily match to republican .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'party_3': 3, 'republican_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'party_3': 'party', 'republican_4': 'republican'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'party_3': [0], 'republican_4': [0]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['ohio 2', 'bill gradison', 'republican', '1974', 're - elected', 'bill gradison ( r ) 68.6 % thomas j porter ( d ) 31.4 %'], ['ohio 3', 'tony p hall', 'democratic', '1978', 're - elected', 'tony p hall ( d ) unopposed'], ['ohio 4', 'mike oxley', 'republican', '1972', 're - elected', 'mike oxley ( r ) 77.5 % william o sutton ( d ) 22.5 %'], ['ohio 5', 'del latta', 'republican', '1958', 're - elected', 'del latta ( r ) 62.7 % james r sherck ( d ) 37.3 %'], ['ohio 6', 'bob mcewen', 'republican', '1980', 're - elected', 'bob mcewen ( r ) 74.0 % bob smith ( d ) 26.0 %'], ['ohio 8', 'tom kindness', 'republican', '1974', 're - elected', 'tom kindness ( r ) 76.9 % john t francis ( d ) 23.1 %'], ['ohio 11', 'dennis e eckart', 'democratic', '1980', 're - elected', 'dennis e eckart ( d ) 66.8 % dean beagle ( r ) 33.2 %'], ['ohio 12', 'john kasich', 'republican', '1982', 're - elected', 'john kasich ( r ) 69.5 % richard s sloan ( d ) 30.5 %'], ['ohio 15', 'chalmers p wylie', 'republican', '1966', 're - elected', 'chalmers p wylie ( r ) 71.6 % duane jager ( d ) 28.4 %'], ['ohio 16', 'ralph regula', 'republican', '1972', 're - elected', 'ralph regula ( r ) 72.4 % james gwin ( d ) 27.6 %']]

xavier malisse

https://en.wikipedia.org/wiki/Xavier_Malisse

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551805-11.html.csv

unique

the 2004 french open was the only win for xavier malisse .

{'scope': 'all', 'row': '3', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': 'w', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2004', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2004 record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; 2004 ; w }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 2004 ; w } }', 'tointer': 'select the rows whose 2004 record fuzzily matches to w . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2004', 'w'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2004 record fuzzily matches to w .', 'tostr': 'filter_eq { all_rows ; 2004 ; w }'}, 'tournament'], 'result': 'french open', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 2004 ; w } ; tournament }'}, 'french open'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 2004 ; w } ; tournament } ; french open }', 'tointer': 'the tournament record of this unqiue row is french open .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 2004 ; w } } ; eq { hop { filter_eq { all_rows ; 2004 ; w } ; tournament } ; french open } } = true', 'tointer': 'select the rows whose 2004 record fuzzily matches to w . there is only one such row in the table . the tournament record of this unqiue row is french open .'}

and { only { filter_eq { all_rows ; 2004 ; w } } ; eq { hop { filter_eq { all_rows ; 2004 ; w } ; tournament } ; french open } } = true

select the rows whose 2004 record fuzzily matches to w . there is only one such row in the table . the tournament record of this unqiue row is french open .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '2004_7': 7, 'w_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'french open_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '2004_7': '2004', 'w_8': 'w', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'french open_10': 'french open'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '2004_7': [0], 'w_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'french open_10': [3]}

['tournament', '2003', '2004', '2012', '2013']

[['grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments', 'grand slam tournaments'], ['australian open', '2r', '2r', '1r', '2r'], ['french open', '2r', 'w', '3r', '1r'], ['wimbledon', '2r', '2r', '1r', '2r'], ['us open', '2r', '1r', '1r', '1r'], ['win - loss', '4 - 4', '8 - 3', '2 - 4', '2 - 4']]

colbie caillat

https://en.wikipedia.org/wiki/Colbie_Caillat

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12416709-3.html.csv

majority

colbie caillat was nominated more times then she won the awards .

{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'nominated', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'nominated'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to nominated .', 'tostr': 'most_eq { all_rows ; result ; nominated } = true'}

most_eq { all_rows ; result ; nominated } = true

for the result records of all rows , most of them fuzzily match to nominated .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'nominated_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'nominated_4': 'nominated'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'nominated_4': [0]}

['year', 'result', 'award', 'category', 'nominated work']

[['2008', 'nominated', 'american music awards', 't - mobile breakthrough artist', 'general'], ['2008', 'nominated', 'teen choice awards', 'choice breakthrough artist', 'general'], ['2008', 'nominated', 'teen choice awards', 'choice love song', 'bubbly'], ['2008', 'won', 'billboard music awards', 'rising star', 'general'], ['2009', 'won', 'bmi pop awards', 'songwriter of the year', 'colbie caillat'], ['2009', 'won', 'bmi pop awards', 'song of the year', 'bubbly'], ['2009', 'nominated', 'teen choice awards', 'choice music : hook up', 'lucky'], ['2010', 'nominated', "people 's choice awards", 'favorite music collaboration', 'lucky']]

2009 thailand national games

https://en.wikipedia.org/wiki/2009_Thailand_National_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18615220-1.html.csv

comparative

suphan buri province won more bronze medals than nonthaburi in the 2009 thailand national games .

{'row_1': '2', 'row_2': '7', 'col': '5', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'province', 'suphan buri'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose province record fuzzily matches to suphan buri .', 'tostr': 'filter_eq { all_rows ; province ; suphan buri }'}, 'bronze'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; province ; suphan buri } ; bronze }', 'tointer': 'select the rows whose province record fuzzily matches to suphan buri . take the bronze record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'province', 'nonthaburi'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose province record fuzzily matches to nonthaburi .', 'tostr': 'filter_eq { all_rows ; province ; nonthaburi }'}, 'bronze'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; province ; nonthaburi } ; bronze }', 'tointer': 'select the rows whose province record fuzzily matches to nonthaburi . take the bronze record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; province ; suphan buri } ; bronze } ; hop { filter_eq { all_rows ; province ; nonthaburi } ; bronze } } = true', 'tointer': 'select the rows whose province record fuzzily matches to suphan buri . take the bronze record of this row . select the rows whose province record fuzzily matches to nonthaburi . take the bronze record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; province ; suphan buri } ; bronze } ; hop { filter_eq { all_rows ; province ; nonthaburi } ; bronze } } = true

select the rows whose province record fuzzily matches to suphan buri . take the bronze record of this row . select the rows whose province record fuzzily matches to nonthaburi . take the bronze record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'province_7': 7, 'suphan buri_8': 8, 'bronze_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'province_11': 11, 'nonthaburi_12': 12, 'bronze_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'province_7': 'province', 'suphan buri_8': 'suphan buri', 'bronze_9': 'bronze', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'province_11': 'province', 'nonthaburi_12': 'nonthaburi', 'bronze_13': 'bronze'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'province_7': [0], 'suphan buri_8': [0], 'bronze_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'province_11': [1], 'nonthaburi_12': [1], 'bronze_13': [3]}

['rank', 'province', 'gold', 'silver', 'bronze', 'total']

[['1', 'bangkok', '129', '114', '80', '323'], ['2', 'suphan buri', '39', '24', '30', '93'], ['3', 'trang', '36', '15', '28', '79'], ['4', 'chonburi', '30', '40', '32', '102'], ['5', 'nakhon ratchasima', '17', '22', '29', '68'], ['6', 'chiang mai', '16', '25', '38', '79'], ['7', 'nonthaburi', '13', '13', '21', '47'], ['8', 'si sa ket', '13', '5', '14', '32'], ['9', 'ubon ratchathani', '12', '8', '25', '45'], ['10', 'samut sakhon', '10', '9', '11', '30']]

2005 masters tournament

https://en.wikipedia.org/wiki/2005_Masters_Tournament

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16147528-2.html.csv

superlative

tigers woods has won more masters tournaments than any other player from the 2005 masters tournament .

{'scope': 'all', 'col_superlative': '3', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'year ( s ) won'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; year ( s ) won }'}, 'player'], 'result': 'tiger woods', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; year ( s ) won } ; player }'}, 'tiger woods'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; year ( s ) won } ; player } ; tiger woods } = true', 'tointer': 'select the row whose year ( s ) won record of all rows is maximum . the player record of this row is tiger woods .'}

eq { hop { argmax { all_rows ; year ( s ) won } ; player } ; tiger woods } = true

select the row whose year ( s ) won record of all rows is maximum . the player record of this row is tiger woods .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'year (s) won_5': 5, 'player_6': 6, 'tiger woods_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'year (s) won_5': 'year ( s ) won', 'player_6': 'player', 'tiger woods_7': 'tiger woods'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'year (s) won_5': [0], 'player_6': [1], 'tiger woods_7': [2]}

['player', 'country', 'year ( s ) won', 'total', 'to par', 'finish']

[['tiger woods', 'united states', '1997 , 2001 , 2002', '276', '- 12', '1'], ['vijay singh', 'fiji', '2000', '284', '- 4', 't5'], ['mike weir', 'canada', '2003', '284', '- 4', 't5'], ['phil mickelson', 'united states', '2004', '285', '- 3', '10'], ['bernhard langer', 'germany', '1985 , 1993', '289', '+ 1', 't20'], ["mark o'meara", 'united states', '1998', '293', '+ 5', 't31'], ['fred couples', 'united states', '1992', '295', '+ 7', 't39'], ['craig stadler', 'united states', '1982', '306', '+ 18', '50']]

2009 nrl season

https://en.wikipedia.org/wiki/2009_NRL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17678435-10.html.csv

aggregation

on average , the winner scored around 55 points in the 2009 nrl season , .

{'scope': 'all', 'col': '3', 'type': 'average', 'result': '55', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'score'], 'result': '55', 'ind': 0, 'tostr': 'avg { all_rows ; score }'}, '55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; score } ; 55 } = true', 'tointer': 'the average of the score record of all rows is 55 .'}

round_eq { avg { all_rows ; score } ; 55 } = true

the average of the score record of all rows is 55 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'score_4': 4, '55_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'score_4': 'score', '55_5': '55'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'score_4': [0], '55_5': [1]}

['team', 'opponent', 'score', 'venue', 'round']

[['brisbane broncos', 'penrith panthers', '58 - 24', 'suncorp stadium', 'round 23'], ['wests tigers', 'cronulla sharks', '56 - 10', 'toyota stadium', 'round 23'], ['canberra raiders', 'brisbane broncos', '56 - 0', 'canberra stadium', 'round 21'], ['wests tigers', 'south sydney rabbitohs', '54 - 20', 'anz stadium', 'round 17'], ['south sydney rabbitohs', 'sydney roosters', '52 - 12', 'sydney football stadium', 'round 1']]

united states house of representatives elections , 1950

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1950

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1342198-17.html.csv

majority

most of the incumbents in the 1950 us house of representatives elections in kentucky were first elected in 1948 .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'equal', 'value': '1948', 'subset': None}

{'func': 'most_eq', 'args': ['all_rows', 'first elected', '1948'], 'result': True, 'ind': 0, 'tointer': 'for the first elected records of all rows , most of them are equal to 1948 .', 'tostr': 'most_eq { all_rows ; first elected ; 1948 } = true'}

most_eq { all_rows ; first elected ; 1948 } = true

for the first elected records of all rows , most of them are equal to 1948 .

1

1

{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'first elected_3': 3, '1948_4': 4}

{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'first elected_3': 'first elected', '1948_4': '1948'}

{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'first elected_3': [0], '1948_4': [0]}

['district', 'incumbent', 'party', 'first elected', 'result', 'candidates']

[['kentucky 1', 'noble jones gregory', 'democratic', '1936', 're - elected', 'noble jones gregory ( d ) unopposed'], ['kentucky 2', 'john a whitaker', 'democratic', '1948', 're - elected', 'john a whitaker ( d ) unopposed'], ['kentucky 4', 'frank chelf', 'democratic', '1944', 're - elected', 'frank chelf ( d ) unopposed'], ['kentucky 6', 'thomas r underwood', 'democratic', '1948', 're - elected', 'thomas r underwood ( d ) unopposed'], ['kentucky 7', 'carl d perkins', 'democratic', '1948', 're - elected', 'carl d perkins ( d ) 56.1 % o w thompson ( r ) 43.9 %'], ['kentucky 8', 'joe b bates', 'democratic', '1930', 're - elected', 'joe b bates ( d ) 60.5 % elmer c roberts ( r ) 39.5 %']]

dwayne bravo

https://en.wikipedia.org/wiki/Dwayne_Bravo

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1376835-2.html.csv

count

for dwayne bravo , when the venue is queen 's park oval , port of spain , there were 2 times the date was in 2006 .

{'scope': 'subset', 'criterion': 'fuzzily_match', 'value': '2006', 'result': '2', 'col': '4', 'subset': {'col': '3', 'criterion': 'equal', 'value': "queen 's park oval , port of spain"}}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', "queen 's park oval , port of spain"], 'result': None, 'ind': 0, 'tostr': "filter_eq { all_rows ; venue ; queen 's park oval , port of spain }", 'tointer': "select the rows whose venue record fuzzily matches to queen 's park oval , port of spain ."}, 'date', '2006'], 'result': None, 'ind': 1, 'tointer': "select the rows whose venue record fuzzily matches to queen 's park oval , port of spain . among these rows , select the rows whose date record fuzzily matches to 2006 .", 'tostr': "filter_eq { filter_eq { all_rows ; venue ; queen 's park oval , port of spain } ; date ; 2006 }"}], 'result': '2', 'ind': 2, 'tostr': "count { filter_eq { filter_eq { all_rows ; venue ; queen 's park oval , port of spain } ; date ; 2006 } }", 'tointer': "select the rows whose venue record fuzzily matches to queen 's park oval , port of spain . among these rows , select the rows whose date record fuzzily matches to 2006 . the number of such rows is 2 ."}, '2'], 'result': True, 'ind': 3, 'tostr': "eq { count { filter_eq { filter_eq { all_rows ; venue ; queen 's park oval , port of spain } ; date ; 2006 } } ; 2 } = true", 'tointer': "select the rows whose venue record fuzzily matches to queen 's park oval , port of spain . among these rows , select the rows whose date record fuzzily matches to 2006 . the number of such rows is 2 ."}

eq { count { filter_eq { filter_eq { all_rows ; venue ; queen 's park oval , port of spain } ; date ; 2006 } } ; 2 } = true

select the rows whose venue record fuzzily matches to queen 's park oval , port of spain . among these rows , select the rows whose date record fuzzily matches to 2006 . the number of such rows is 2 .

4

4

{'eq_3': 3, 'result_4': 4, 'count_2': 2, 'filter_str_eq_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'venue_6': 6, "queen 's park oval , port of spain_7": 7, 'date_8': 8, '2006_9': 9, '2_10': 10}

{'eq_3': 'eq', 'result_4': 'true', 'count_2': 'count', 'filter_str_eq_1': 'filter_str_eq', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'venue_6': 'venue', "queen 's park oval , port of spain_7": "queen 's park oval , port of spain", 'date_8': 'date', '2006_9': '2006', '2_10': '2'}

{'eq_3': [4], 'result_4': [], 'count_2': [3], 'filter_str_eq_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'venue_6': [0], "queen 's park oval , port of spain_7": [0], 'date_8': [1], '2006_9': [1], '2_10': [3]}

['s no', 'opponent', 'venue', 'date', 'match performance']

[['1', 'england', 'trent bridge , nottingham', '27 june 2004', '10 - 2 - 26 - 3 , dnb'], ['2', 'india', "queen 's park oval , port of spain", '26 may 2006', '5 - 0 - 32 - 3 , 61 ( 62 balls : 3x4 , 1x6 )'], ['3', 'india', "queen 's park oval , port of spain", '28 may 2006', '62 ( 44 balls : 4x4 ) , 9 - 0 - 45 - 0'], ['4', 'sri lanka', "queen 's park oval , port of spain", '10 april 2008', '10 - 1 - 32 - 4 , 1 catch , 36 ( 37 balls : 3x4 , 2x6 )'], ['5', 'england', 'kensington oval , bridgetown', '27 march 2009', '7 - 1 - 19 - 4 , 1 catch , dnb'], ['6', 'zimbabwe', 'arnos vale stadium , kingstown', '12 march 2010', '9 - 2 - 21 - 4 , 6 ( 8 balls : 1x4 )'], ['7', 'zimbabwe', "national cricket stadium , st george 's", '24 february 2013', '10 - 1 - 43 - 6 , 0 ( 2 balls )']]

1972 isle of man tt

https://en.wikipedia.org/wiki/1972_Isle_of_Man_TT

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15753390-4.html.csv

superlative

the rider chas mortimer achieved the fastest time of all the participants .

{'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': ['all_rows', 'time'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; time }'}, 'rider'], 'result': 'chas mortimer', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; time } ; rider }'}, 'chas mortimer'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; time } ; rider } ; chas mortimer } = true', 'tointer': 'select the row whose time record of all rows is minimum . the rider record of this row is chas mortimer .'}

eq { hop { argmin { all_rows ; time } ; rider } ; chas mortimer } = true

select the row whose time record of all rows is minimum . the rider record of this row is chas mortimer .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'time_5': 5, 'rider_6': 6, 'chas mortimer_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'time_5': 'time', 'rider_6': 'rider', 'chas mortimer_7': 'chas mortimer'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'time_5': [0], 'rider_6': [1], 'chas mortimer_7': [2]}

['place', 'rider', 'country', 'machine', 'speed', 'time', 'points']

[['1', 'chas mortimer', 'united kingdom', 'yamaha', '87.49 mph', '1:17.38.2', '15'], ['2', 'charlie williams', 'united kingdom', 'yamaha', '80.49 mph', '1:24.23.0', '12'], ['3', 'billy rae', 'united kingdom', 'maico', '79.29 mph', '1:25.39.8', '10'], ['4', 'lindsay porter', 'united kingdom', 'honda', '78.63 mph', '1:26.30.0', '8'], ['5', 'ron hackett', 'united kingdom', 'honda', '76.55 mph', '1:28.44.0', '6'], ['6', 'ralph watts', 'united kingdom', 'honda', '76.40 mph', '1:28.54.0', '5'], ['7', 'fred launchbury', 'united kingdom', 'maico', '75.75 mph', '1:29.40.60', '4'], ['8', 'leigh notman', 'united kingdom', 'yamaha', '75.74 mph', '1:29.41.40', '3'], ['9', 'amorris', 'united kingdom', 'yamaha', '75.70 mph', '1:29.43.60', '2'], ['10', 'mevans', 'united kingdom', 'yamaha', '75.23 mph', '1:30.17.40', '1']]

b " list of r. l. stine 's the haunting hour episodes "

https://en.wikipedia.org/wiki/List_of_R._L._Stine%27s_The_Haunting_Hour_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-29196086-4.html.csv

count

there are 12 listed episodes in the r. l. stine 's the haunting hour series .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '12', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'no in series'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose no in series record is arbitrary .', 'tostr': 'filter_all { all_rows ; no in series }'}], 'result': '12', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; no in series } }', 'tointer': 'select the rows whose no in series record is arbitrary . the number of such rows is 12 .'}, '12'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; no in series } } ; 12 } = true', 'tointer': 'select the rows whose no in series record is arbitrary . the number of such rows is 12 .'}

eq { count { filter_all { all_rows ; no in series } } ; 12 } = true

select the rows whose no in series record is arbitrary . the number of such rows is 12 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'no in series_5': 5, '12_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'no in series_5': 'no in series', '12_6': '12'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'no in series_5': [0], '12_6': [2]}

['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date']

[['41', '1', 'grampires ( part 1 )', 'neill fearnley', 'erik patterson & jessica scott', 'october 13 , 2012'], ['42', '2', 'grampires ( part 2 )', 'neill fearnley', 'erik patterson & jessica scott', 'october 13 , 2012'], ['43', '3', 'the cast', 'ken friss', 'craig s phillips & harold hayes jr', 'october 20 , 2012'], ['44', '4', 'the weeping woman', 'neill fearnley', 'harold hayes jr & craig s phillips', 'october 27 , 2012'], ['45', '5', 'intruders', 'ken friss', 'jack monaco', 'november 3 , 2012'], ['47', '7', 'red eye', 'ken friss', 'natalie lapointe & greg yolen', 'november 17 , 2012'], ['48', '8', 'my imaginary friend', 'james head', 'melody fox', 'november 24 , 2012'], ['49', '9', 'poof de fromage', 'ken friss', 'erik patterson & jessica scott', 'december 1 , 2012'], ['50', '10', 'the golem ( part 1 )', 'neill fearnley', 'jack monaco', 'december 8 , 2012'], ['51', '11', 'the golem ( part 2 )', 'neill fearnley', 'jack monaco', 'december 8 , 2012'], ['52', '12', 'the girl in the painting', 'ken friss', 'jack monaco', 'december 15 , 2012'], ['53', '13', 'checking out', 'james head', 'melody fox', 'january 19 , 2013']]

1988 concacaf champions ' cup

https://en.wikipedia.org/wiki/1988_CONCACAF_Champions%27_Cup

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12285359-7.html.csv

ordinal

defence force was the second highest aggregate scoring team in the 1988 concacaf champions ' cup .

{'row': '3', 'col': '2', 'order': '2', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'agg', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; agg ; 2 }'}, 'team 2'], 'result': 'defence force', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; agg ; 2 } ; team 2 }'}, 'defence force'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; agg ; 2 } ; team 2 } ; defence force } = true', 'tointer': 'select the row whose agg record of all rows is 2nd maximum . the team 2 record of this row is defence force .'}

eq { hop { nth_argmax { all_rows ; agg ; 2 } ; team 2 } ; defence force } = true

select the row whose agg record of all rows is 2nd maximum . the team 2 record of this row is defence force .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'agg_5': 5, '2_6': 6, 'team 2_7': 7, 'defence force_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'agg_5': 'agg', '2_6': '2', 'team 2_7': 'team 2', 'defence force_8': 'defence force'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'agg_5': [0], '2_6': [0], 'team 2_7': [1], 'defence force_8': [2]}

['team 1', 'agg', 'team 2', '1st leg', '2nd leg']

[['rksv centro dominguito', '1 - 3', 'gauloise de basse - terre', '1 - 1', '0 - 2'], ['seba united', '5 - 2', 'undeba', '3 - 0', '2 - 2'], ['club franciscain', '2 - 4', 'defence force', '2 - 2', '0 - 2'], ['trintoc', '1 - 2', 'excelsior ( schoelcher )', '1 - 1', '0 - 1'], ['sv leo victor', '2 - 3', 'asl sport guyanais', '2 - 1', '0 - 2']]

statistics relating to enlargement of the european union

https://en.wikipedia.org/wiki/Statistics_relating_to_enlargement_of_the_European_Union

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1307842-7.html.csv

unique

malta is the only member country of the european union with an enlarged area ( km square ) that is less than 1000 .

{'scope': 'all', 'row': '7', 'col': '3', 'col_other': '1', 'criterion': 'less_than', 'value': '1000', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '1000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area ( km square ) record is less than 1000 .', 'tostr': 'filter_less { all_rows ; area ( km square ) ; 1000 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_less { all_rows ; area ( km square ) ; 1000 } }', 'tointer': 'select the rows whose area ( km square ) record is less than 1000 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'area ( km square )', '1000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose area ( km square ) record is less than 1000 .', 'tostr': 'filter_less { all_rows ; area ( km square ) ; 1000 }'}, 'member countries'], 'result': 'malta', 'ind': 2, 'tostr': 'hop { filter_less { all_rows ; area ( km square ) ; 1000 } ; member countries }'}, 'malta'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_less { all_rows ; area ( km square ) ; 1000 } ; member countries } ; malta }', 'tointer': 'the member countries record of this unqiue row is malta .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_less { all_rows ; area ( km square ) ; 1000 } } ; eq { hop { filter_less { all_rows ; area ( km square ) ; 1000 } ; member countries } ; malta } } = true', 'tointer': 'select the rows whose area ( km square ) record is less than 1000 . there is only one such row in the table . the member countries record of this unqiue row is malta .'}

and { only { filter_less { all_rows ; area ( km square ) ; 1000 } } ; eq { hop { filter_less { all_rows ; area ( km square ) ; 1000 } ; member countries } ; malta } } = true

select the rows whose area ( km square ) record is less than 1000 . there is only one such row in the table . the member countries record of this unqiue row is malta .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_less_0': 0, 'all_rows_6': 6, 'area (km square)_7': 7, '1000_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'member countries_9': 9, 'malta_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_less_0': 'filter_less', 'all_rows_6': 'all_rows', 'area (km square)_7': 'area ( km square )', '1000_8': '1000', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'member countries_9': 'member countries', 'malta_10': 'malta'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_less_0': [1, 2], 'all_rows_6': [0], 'area (km square)_7': [0], '1000_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'member countries_9': [2], 'malta_10': [3]}

['member countries', 'population', 'area ( km square )', 'gdp ( billion us )', 'gdp per capita ( us )']

[['cyprus', '775927', '9250', '11.681', '15054'], ['czech republic', '10246178', '78866', '105.248', '10272'], ['estonia', '1341664', '45226', '22.384', '16684'], ['hungary', '10032375', '93030', '102183', '10185'], ['latvia', '2306306', '64589', '24.826', '10764'], ['lithuania', '3607899', '65200', '31.971', '8861'], ['malta', '396851', '316', '5.097', '12843'], ['poland', '38580445', '311904', '316.438', '8202'], ['slovakia', '5423567', '49036', '42.800', '7810'], ['slovenia', '2011473', '20273', '29.633', '14732'], ['accession countries', '74722685', '737690', '685.123', '9169'], ['existing members ( 2004 )', '381781620', '3367154', '7711.871', '20200'], ['eu25 ( 2004 )', '456504305 ( + 19.57 % )', '4104844 ( + 17.97 % )', '8396994 ( + 8.88 % )', '18394 ( 8.94 % )']]

moroccan grand prix

https://en.wikipedia.org/wiki/Moroccan_Grand_Prix

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1167997-1.html.csv

majority

in the moroccan grand prix , when the location is casablanca , all of the categories are a touring car .

{'scope': 'subset', 'col': '4', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'touring car', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'casablanca'}}

{'func': 'all_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'casablanca'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; casablanca }', 'tointer': 'select the rows whose location record fuzzily matches to casablanca .'}, 'category', 'touring car'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to casablanca . for the category records of these rows , all of them fuzzily match to touring car .', 'tostr': 'all_eq { filter_eq { all_rows ; location ; casablanca } ; category ; touring car } = true'}

all_eq { filter_eq { all_rows ; location ; casablanca } ; category ; touring car } = true

select the rows whose location record fuzzily matches to casablanca . for the category records of these rows , all of them fuzzily match to touring car .

2

2

{'all_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location_4': 4, 'casablanca_5': 5, 'category_6': 6, 'touring car_7': 7}

{'all_str_eq_1': 'all_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location_4': 'location', 'casablanca_5': 'casablanca', 'category_6': 'category', 'touring car_7': 'touring car'}

{'all_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location_4': [0], 'casablanca_5': [0], 'category_6': [1], 'touring car_7': [1]}

['year', 'driver', 'constructor', 'category', 'location', 'report']

[['1958', 'stirling moss', 'vanwall', 'formula one', 'ain - diab', 'report'], ['1957', 'jean behra', 'maserati', 'formula one', 'ain - diab', 'report'], ['1956', 'maurice trintignant', 'ferrari', 'sports cars', 'agadir', 'report'], ['1955', 'mike sparken', 'ferrari', 'sports cars', 'agadir', 'report'], ['1954', 'giuseppe farina', 'ferrari', 'sports cars', 'agadir', 'report'], ['1953 - 1935', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1934', 'louis chiron', 'alfa romeo', 's touring car', 'anfa', 'report'], ['1933', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1932', 'marcel lehoux', 'bugatti', 's touring car', 'anfa', 'report'], ['1931', 'stanisław czaykowski', 'bugatti', 's touring car', 'anfa', 'report'], ['1930', 'charles bénitah', 'amilcar', 's touring car', 'anfa', 'report'], ['1929', 'not held', 'not held', 'not held', 'not held', 'not held'], ['1928', 'e meyer', 'bugatti', 's touring car', 'casablanca', 'report'], ['1927', 'g roll', 'georges irat', 's touring car', 'casablanca', 'report'], ['1926', 'r meyerl', 'bugatti', 's touring car', 'casablanca', 'report'], ['1925', 'comte de vaugelas', 'delage', 's touring car', 'casablanca', 'report']]

2008 - 09 new york rangers season

https://en.wikipedia.org/wiki/2008%E2%80%9309_New_York_Rangers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17360905-6.html.csv

majority

the majority of these games resulted in a decision of " lundquist . " .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'lundqvist', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'decision', 'lundqvist'], 'result': True, 'ind': 0, 'tointer': 'for the decision records of all rows , most of them fuzzily match to lundqvist .', 'tostr': 'most_eq { all_rows ; decision ; lundqvist } = true'}

most_eq { all_rows ; decision ; lundqvist } = true

for the decision records of all rows , most of them fuzzily match to lundqvist .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'decision_3': 3, 'lundqvist_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'decision_3': 'decision', 'lundqvist_4': 'lundqvist'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'decision_3': [0], 'lundqvist_4': [0]}

['game', 'january', 'opponent', 'score', 'decision', 'record']

[['40', '3', 'washington capitals', '2 - 1', 'valiquette', '23 - 14 - 3'], ['41', '5', 'pittsburgh penguins', '4 - 0', 'lundqvist', '24 - 14 - 3'], ['42', '7', 'montreal canadiens', '6 - 3', 'lundqvist', '24 - 15 - 3'], ['43', '9', 'buffalo sabres', '2 - 1 so', 'valiquette', '24 - 15 - 4'], ['44', '10', 'ottawa senators', '2 - 0', 'lundqvist', '25 - 15 - 4'], ['45', '13', 'new york islanders', '2 - 1', 'lundqvist', '26 - 15 - 4'], ['46', '16', 'chicago blackhawks', '3 - 2 ot', 'lundqvist', '27 - 15 - 4'], ['47', '18', 'pittsburgh penguins', '3 - 0', 'lundqvist', '27 - 16 - 4'], ['48', '20', 'anaheim ducks', '4 - 2', 'lundqvist', '28 - 16 - 4'], ['49', '27', 'carolina hurricanes', '3 - 2', 'valiquette', '29 - 16 - 4'], ['50', '28', 'pittsburgh penguins', '6 - 2', 'lundqvist', '29 - 17 - 4'], ['51', '31', 'boston bruins', '1 - 0', 'lundqvist', '29 - 18 - 4']]

1940 in brazilian football

https://en.wikipedia.org/wiki/1940_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15349635-2.html.csv

aggregation

the average number of games that were drawn in 1940 in brazilian football was 2.55 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '2.55', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'drawn'], 'result': '2.55', 'ind': 0, 'tostr': 'avg { all_rows ; drawn }'}, '2.55'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; drawn } ; 2.55 } = true', 'tointer': 'the average of the drawn record of all rows is 2.55 .'}

round_eq { avg { all_rows ; drawn } ; 2.55 } = true

the average of the drawn record of all rows is 2.55 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'drawn_4': 4, '2.55_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'drawn_4': 'drawn', '2.55_5': '2.55'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'drawn_4': [0], '2.55_5': [1]}

['position', 'team', 'points', 'played', 'drawn', 'lost', 'against', 'difference']

[['1', 'palestra itália - sp', '33', '20', '3', '2', '19', '34'], ['2', 'portuguesa', '30', '20', '4', '3', '24', '22'], ['3', 'ypiranga - sp', '27', '20', '1', '6', '37', '19'], ['4', 'corinthians', '26', '20', '2', '6', '31', '23'], ['5', 'portuguesa santista', '25', '20', '3', '6', '40', '13'], ['6', 'são paulo', '19', '20', '1', '10', '41', '1'], ['7', 'santos', '18', '20', '4', '9', '49', '2'], ['8', 'são paulo railway', '16', '20', '6', '9', '50', '- 6'], ['9', 'hespanha', '10', '20', '0', '15', '47', '- 22'], ['10', 'comercial - sp', '9', '20', '3', '14', '72', '- 47'], ['11', 'juventus', '7', '20', '1', '16', '68', '- 39']]

sébastien bourdais

https://en.wikipedia.org/wiki/S%C3%A9bastien_Bourdais

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1019053-15.html.csv

comparative

sébastien bourdais had a higher number of points on the grand-am rolex sports car series in the year of 2013 compared to the year of 2006 .

{'row_1': '5', 'row_2': '2', 'col': '7', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2013'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2013 .', 'tostr': 'filter_eq { all_rows ; year ; 2013 }'}, 'points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2013 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 2013 . take the points record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2006'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2006 .', 'tostr': 'filter_eq { all_rows ; year ; 2006 }'}, 'points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2006 } ; points }', 'tointer': 'select the rows whose year record fuzzily matches to 2006 . take the points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 2013 } ; points } ; hop { filter_eq { all_rows ; year ; 2006 } ; points } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 2013 . take the points record of this row . select the rows whose year record fuzzily matches to 2006 . take the points record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; year ; 2013 } ; points } ; hop { filter_eq { all_rows ; year ; 2006 } ; points } } = true

select the rows whose year record fuzzily matches to 2013 . take the points record of this row . select the rows whose year record fuzzily matches to 2006 . take the points record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2013_8': 8, 'points_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '2006_12': 12, 'points_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2013_8': '2013', 'points_9': 'points', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2006_12': '2006', 'points_13': 'points'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '2013_8': [0], 'points_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '2006_12': [1], 'points_13': [3]}

['year', 'team', 'make', 'engine', 'class', 'rank', 'points']

[['2005', 'newman racing / silverstone racing', 'crawford dp03', 'ford', 'dp', '89th', '6'], ['2006', 'doran racing', 'doran je4', 'ford', 'dp', '108th', '3'], ['2010', 'crown royal / npn racing', 'riley mk xi', 'bmw 5.0 l v8', 'dp', 'nc', '0'], ['2012', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '17th', '97'], ['2013', 'starworks motorsport', 'riley mk xxvi', 'ford', 'dp', '18th', '160']]

spain men 's national water polo team

https://en.wikipedia.org/wiki/Spain_men%27s_national_water_polo_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18985137-1.html.csv

unique

xavier garcía is the only player that previously played on vk primorje rijeka .

{'scope': 'all', 'row': '12', 'col': '5', 'col_other': '1', 'criterion': 'equal', 'value': 'vk primorje rijeka', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2012 club', 'vk primorje rijeka'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2012 club record fuzzily matches to vk primorje rijeka .', 'tostr': 'filter_eq { all_rows ; 2012 club ; vk primorje rijeka }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } }', 'tointer': 'select the rows whose 2012 club record fuzzily matches to vk primorje rijeka . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', '2012 club', 'vk primorje rijeka'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose 2012 club record fuzzily matches to vk primorje rijeka .', 'tostr': 'filter_eq { all_rows ; 2012 club ; vk primorje rijeka }'}, 'name'], 'result': 'xavier garcía', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } ; name }'}, 'xavier garcía'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } ; name } ; xavier garcía }', 'tointer': 'the name record of this unqiue row is xavier garcía .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } } ; eq { hop { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } ; name } ; xavier garcía } } = true', 'tointer': 'select the rows whose 2012 club record fuzzily matches to vk primorje rijeka . there is only one such row in the table . the name record of this unqiue row is xavier garcía .'}

and { only { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } } ; eq { hop { filter_eq { all_rows ; 2012 club ; vk primorje rijeka } ; name } ; xavier garcía } } = true

select the rows whose 2012 club record fuzzily matches to vk primorje rijeka . there is only one such row in the table . the name record of this unqiue row is xavier garcía .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, '2012 club_7': 7, 'vk primorje rijeka_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'name_9': 9, 'xavier garcía_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', '2012 club_7': '2012 club', 'vk primorje rijeka_8': 'vk primorje rijeka', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_9': 'name', 'xavier garcía_10': 'xavier garcía'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], '2012 club_7': [0], 'vk primorje rijeka_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'name_9': [2], 'xavier garcía_10': [3]}

['name', 'pos', 'height', 'weight', '2012 club']

[['iñaki aguilar', 'gk', 'm', '-', 'cn sabadell'], ['mario josé garcía', 'd', 'm', '-', 'real canoe'], ['david martín', 'd', 'm', '-', 'cn atlètic - barceloneta'], ['balázs szirányi', 'cf', 'm', '-', 'real canoe'], ['guillermo molina', 'cf', 'm', '-', 'pro recco'], ['marc minguell', 'cf', 'm', '-', 'posillipo'], ['blai mallarach', 'cf', 'm', '-', 'havk mladost'], ['albert español', 'd', 'm', '-', 'cn atlètic - barceloneta'], ['xavier vallès', 'cf', 'm', '-', 'cn atlètic - barceloneta'], ['felipe perrone', 'd', 'm', '-', 'pro recco'], ['iván pérez', 'cf', 'm', '-', 'cn sabadell'], ['xavier garcía', 'cf', 'm', '-', 'vk primorje rijeka'], ['daniel lópez', 'gk', 'm', '-', 'cn atlètic - barceloneta']]

history of george mason basketball

https://en.wikipedia.org/wiki/History_of_George_Mason_basketball

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16835332-1.html.csv

ordinal

jim larranaga had the second highest win percentage of the coaches in george mason basketball .

{'row': '8', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'win %', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; win % ; 2 }'}, 'coach'], 'result': 'jim larranaga', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; win % ; 2 } ; coach }'}, 'jim larranaga'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; win % ; 2 } ; coach } ; jim larranaga } = true', 'tointer': 'select the row whose win % record of all rows is 2nd maximum . the coach record of this row is jim larranaga .'}

eq { hop { nth_argmax { all_rows ; win % ; 2 } ; coach } ; jim larranaga } = true

select the row whose win % record of all rows is 2nd maximum . the coach record of this row is jim larranaga .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'win %_5': 5, '2_6': 6, 'coach_7': 7, 'jim larranaga_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'win %_5': 'win %', '2_6': '2', 'coach_7': 'coach', 'jim larranaga_8': 'jim larranaga'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'win %_5': [0], '2_6': [0], 'coach_7': [1], 'jim larranaga_8': [2]}

['coach', 'years', 'win - loss', 'win %', 'conference titles']

[['arnold siegfried', '1966 - 1967', '6 - 12', '333', '0'], ['raymond spuhler', '1967 - 1970', '11 - 60', '155', '0'], ['john linn', '1970 - 1980', '130 - 147', '469', '0'], ['joe harrington', '1980 - 1987', '112 - 85', '569', '0'], ['rick barnes', '1987 - 1988', '20 - 10', '667', '0'], ['ernie nestor', '1988 - 1993', '68 - 81', '456', '1'], ['paul westhead', '1993 - 1997', '38 - 70', '352', '0'], ['jim larranaga', '1997 - 2011', '207 - 131', '612', '3'], ['paul hewitt', '2011 - present', '0 - 0', 'n / a', 'n / a']]

wru division one west

https://en.wikipedia.org/wiki/WRU_Division_One_West

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12792876-2.html.csv

superlative

in wru division one west , the club bridgend ravens had the most tries for .

{'scope': 'all', 'col_superlative': '7', 'row_superlative': '2', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'tries for'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; tries for }'}, 'club'], 'result': 'bridgend ravens', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; tries for } ; club }'}, 'bridgend ravens'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; tries for } ; club } ; bridgend ravens } = true', 'tointer': 'select the row whose tries for record of all rows is maximum . the club record of this row is bridgend ravens .'}

eq { hop { argmax { all_rows ; tries for } ; club } ; bridgend ravens } = true

select the row whose tries for record of all rows is maximum . the club record of this row is bridgend ravens .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'tries for_5': 5, 'club_6': 6, 'bridgend ravens_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'tries for_5': 'tries for', 'club_6': 'club', 'bridgend ravens_7': 'bridgend ravens'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'tries for_5': [0], 'club_6': [1], 'bridgend ravens_7': [2]}

['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']

[['club', 'played', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['bridgend ravens', '22', '1', '1', '848', '337', '108', '30', '13', '1', '96'], ['narberth rfc', '22', '1', '8', '726', '443', '92', '53', '12', '5', '71'], ['bridgend athletic rfc', '22', '3', '5', '564', '486', '61', '55', '5', '1', '68'], ['bonymaen rfc', '22', '2', '6', '478', '464', '55', '55', '5', '3', '68'], ['corus ( port talbot ) rfc', '22', '1', '8', '576', '544', '73', '58', '10', '4', '68'], ['uwic rfc', '22', '1', '9', '624', '559', '80', '66', '10', '4', '64'], ['whitland rfc', '22', '2', '9', '550', '460', '69', '49', '6', '3', '57'], ['carmarthen athletic rfc', '22', '3', '10', '509', '554', '64', '69', '6', '2', '50'], ['llangennech rfc', '22', '0', '14', '402', '577', '46', '69', '4', '3', '39'], ['waunarlwydd rfc', '22', '0', '16', '505', '602', '48', '75', '3', '10', '37'], ['maesteg rfc', '22', '0', '19', '427', '714', '43', '91', '2', '5', '19'], ['felinfoel rfc', '22', '2', '19', '334', '803', '43', '112', '3', '5', '16']]

wru division one north

https://en.wikipedia.org/wiki/WRU_Division_One_North

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14058433-3.html.csv

comparative

in wru division one north , mold rfc won 3 more games than ruthin rfc .

{'row_1': '4', 'row_2': '7', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '3', 'bigger': 'row1'}}

{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'mold rfc'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose club record fuzzily matches to mold rfc .', 'tostr': 'filter_eq { all_rows ; club ; mold rfc }'}, 'won'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; club ; mold rfc } ; won }', 'tointer': 'select the rows whose club record fuzzily matches to mold rfc . take the won record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'club', 'ruthin rfc'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose club record fuzzily matches to ruthin rfc .', 'tostr': 'filter_eq { all_rows ; club ; ruthin rfc }'}, 'won'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; club ; ruthin rfc } ; won }', 'tointer': 'select the rows whose club record fuzzily matches to ruthin rfc . take the won record of this row .'}], 'result': '3', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; club ; mold rfc } ; won } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; won } }'}, '3'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; club ; mold rfc } ; won } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; won } } ; 3 } = true', 'tointer': 'select the rows whose club record fuzzily matches to mold rfc . take the won record of this row . select the rows whose club record fuzzily matches to ruthin rfc . take the won record of this row . the first record is 3 larger than the second record .'}

eq { diff { hop { filter_eq { all_rows ; club ; mold rfc } ; won } ; hop { filter_eq { all_rows ; club ; ruthin rfc } ; won } } ; 3 } = true

select the rows whose club record fuzzily matches to mold rfc . take the won record of this row . select the rows whose club record fuzzily matches to ruthin rfc . take the won record of this row . the first record is 3 larger than the second record .

6

6

{'eq_5': 5, 'result_6': 6, 'diff_4': 4, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'club_8': 8, 'mold rfc_9': 9, 'won_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'club_12': 12, 'ruthin rfc_13': 13, 'won_14': 14, '3_15': 15}

{'eq_5': 'eq', 'result_6': 'true', 'diff_4': 'diff', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'club_8': 'club', 'mold rfc_9': 'mold rfc', 'won_10': 'won', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'club_12': 'club', 'ruthin rfc_13': 'ruthin rfc', 'won_14': 'won', '3_15': '3'}

{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'club_8': [0], 'mold rfc_9': [0], 'won_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'club_12': [1], 'ruthin rfc_13': [1], 'won_14': [3], '3_15': [5]}

['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points']

[['club', 'played', 'won', 'drawn', 'lost', 'points for', 'points against', 'tries for', 'tries against', 'try bonus', 'losing bonus', 'points'], ['nant conwy rfc', '18', '17', '0', '1', '578', '183', '83', '19', '11', '1', '80'], ['caernarfon rfc', '18', '17', '0', '1', '570', '179', '81', '21', '11', '0', '79'], ['mold rfc', '18', '11', '0', '7', '471', '349', '63', '46', '8', '3', '55'], ['pwllheli rfc', '18', '10', '0', '8', '479', '338', '66', '42', '7', '4', '51'], ['bro ffestiniog rfc', '18', '9', '0', '9', '346', '457', '52', '63', '5', '2', '43'], ['ruthin rfc', '18', '8', '1', '9', '352', '381', '49', '46', '4', '1', '39'], ['colwyn bay rfc', '18', '5', '1', '12', '293', '402', '37', '55', '4', '5', '31'], ['llandudno rfc', '18', '4', '2', '12', '266', '536', '30', '79', '2', '4', '26'], ['llangefni rfc', '18', '4', '0', '14', '267', '423', '27', '58', '3', '5', '24'], ['denbigh rfc', '18', '3', '0', '15', '204', '578', '24', '83', '1', '3', '16']]

2008 - 09 cleveland cavaliers season

https://en.wikipedia.org/wiki/2008%E2%80%9309_Cleveland_Cavaliers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17325580-10.html.csv

comparative

lebron james scored more points than daniel gibson did on april 2 .

{'row_1': '1', 'row_2': '8', 'col': '5', 'col_other': '2', 'relation': 'not_equal', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'not_str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 2'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to april 2 .', 'tostr': 'filter_eq { all_rows ; date ; april 2 }'}, 'high points'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; april 2 } ; high points }', 'tointer': 'select the rows whose date record fuzzily matches to april 2 . take the high points record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'april 15'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to april 15 .', 'tostr': 'filter_eq { all_rows ; date ; april 15 }'}, 'high points'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; april 15 } ; high points }', 'tointer': 'select the rows whose date record fuzzily matches to april 15 . take the high points record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'not_eq { hop { filter_eq { all_rows ; date ; april 2 } ; high points } ; hop { filter_eq { all_rows ; date ; april 15 } ; high points } } = true', 'tointer': 'select the rows whose date record fuzzily matches to april 2 . take the high points record of this row . select the rows whose date record fuzzily matches to april 15 . take the high points record of this row . the first record does not match to the second record .'}

not_eq { hop { filter_eq { all_rows ; date ; april 2 } ; high points } ; hop { filter_eq { all_rows ; date ; april 15 } ; high points } } = true

select the rows whose date record fuzzily matches to april 2 . take the high points record of this row . select the rows whose date record fuzzily matches to april 15 . take the high points record of this row . the first record does not match to the second record .

5

5

{'not_str_eq_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, 'april 2_8': 8, 'high points_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'april 15_12': 12, 'high points_13': 13}

{'not_str_eq_4': 'not_str_eq', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', 'april 2_8': 'april 2', 'high points_9': 'high points', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'april 15_12': 'april 15', 'high points_13': 'high points'}

{'not_str_eq_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'april 2_8': [0], 'high points_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'april 15_12': [1], 'high points_13': [3]}

['game', 'date', 'team', 'score', 'high points', 'high rebounds', 'high assists', 'location attendance', 'record']

[['75', 'april 2', 'washington', 'l 101 - 109 ( ot )', 'lebron james ( 31 )', 'lebron james ( 9 )', 'delonte west ( 7 )', 'verizon center 20173', '61 - 14'], ['76', 'april 3', 'orlando', 'l 87 - 116 ( ot )', 'lebron james ( 26 )', 'lebron james ( 9 )', 'lebron james ( 5 )', 'amway arena 17461', '61 - 15'], ['77', 'april 5', 'san antonio', 'w 101 - 81 ( ot )', 'lebron james ( 38 )', 'žydrūnas ilgauskas ( 10 )', 'lebron james ( 6 )', 'quicken loans arena 20562', '62 - 15'], ['78', 'april 8', 'washington', 'w 98 - 86 ( ot )', 'lebron james ( 21 )', 'žydrūnas ilgauskas ( 13 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '63 - 15'], ['79', 'april 10', 'philadelphia', 'w 102 - 92 ( ot )', 'lebron james ( 27 )', 'žydrūnas ilgauskas ( 9 )', 'lebron james ( 10 )', 'wachovia center 20484', '64 - 15'], ['80', 'april 12', 'boston', 'w 107 - 76 ( ot )', 'lebron james ( 29 )', 'žydrūnas ilgauskas ( 10 )', 'lebron james ( 7 )', 'quicken loans arena 20562', '65 - 15'], ['81', 'april 13', 'indiana', 'w 117 - 109 ( ot )', 'lebron james ( 37 )', 'anderson varejão ( 11 )', 'maurice williams ( 8 )', 'conseco fieldhouse 18165', '66 - 15'], ['82', 'april 15', 'philadelphia', 'l 110 - 111 ( ot )', 'daniel gibson ( 28 )', 'darnell jackson , wally szczerbiak ( 8 )', 'wally szczerbiak ( 8 )', 'quicken loans arena 20562', '66 - 16']]

list of w \ xc3 \ xbcrttemberg locomotives and railbuses

https://en.wikipedia.org/wiki/List_of_W%C3%BCrttemberg_locomotives_and_railbuses

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18934662-10.html.csv

count

of the wurttemburg locomotives and railbuses , 3 classes are de ( deutsch ) .

{'scope': 'all', 'criterion': 'equal', 'value': 'de', 'result': '3', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'class', 'de'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose class record fuzzily matches to de .', 'tostr': 'filter_eq { all_rows ; class ; de }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; class ; de } }', 'tointer': 'select the rows whose class record fuzzily matches to de . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; class ; de } } ; 3 } = true', 'tointer': 'select the rows whose class record fuzzily matches to de . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; class ; de } } ; 3 } = true

select the rows whose class record fuzzily matches to de . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'class_5': 5, 'de_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'class_5': 'class', 'de_6': 'de', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'class_5': [0], 'de_6': [0], '3_7': [2]}

['class', 'railway number ( s )', 'quantity', 'year ( s ) of manufacture', 'type']

[['bw', '1 - 5', '5', '1887 - 1900', 'a1 bm'], ['dw ( de )', '1 - 5', '5', '1895 - 1901', 'a1 n2'], ['dw ( de )', '6 - 17', '12', '1903 - 1909', 'a1 h2'], ['aw', '1', '( 1 )', '( 1897 )', 'bo ′ 2 ′ g2t'], ['dwss ( de )', '1', '1', '1907', '( 1a ) 2 ′ h2']]

ádammo

https://en.wikipedia.org/wiki/%C3%81dammo

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27501971-2.html.csv

count

the band adammo won the rock group of the year category twice .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'rock group', 'result': '2', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'categoría', 'rock group'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose categoría record fuzzily matches to rock group .', 'tostr': 'filter_eq { all_rows ; categoría ; rock group }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; categoría ; rock group } }', 'tointer': 'select the rows whose categoría record fuzzily matches to rock group . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; categoría ; rock group } } ; 2 } = true', 'tointer': 'select the rows whose categoría record fuzzily matches to rock group . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; categoría ; rock group } } ; 2 } = true

select the rows whose categoría record fuzzily matches to rock group . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'categoría_5': 5, 'rock group_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'categoría_5': 'categoría', 'rock group_6': 'rock group', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'categoría_5': [0], 'rock group_6': [0], '2_7': [2]}

['año', 'trabajo nominado', 'premio', 'categoría', 'country', 'resultado']

[['2009', 'adammo', 'mtv latin america', 'revelation artist', 'colombia', 'nominate'], ['2009', 'adammo', 'mtv latin america', 'best new artist : center', 'colombia', 'winner'], ['2009', 'adammo', 'mtv latin america', 'prize zone', 'colombia', 'nominate'], ['2010', 'adammo', 'premios apdayc', 'rock group of the year', 'perú', 'winner'], ['2010', 'adammo', 'premios apdayc', 'artist of the year', 'perú', 'nominate'], ['2010', 'adammo', 'premios orgullosamente latino', 'grupo latin of the year', 'mexico', 'nominate'], ['2010', 'algún día', 'latin grammy awards', 'short video of the year', 'eeuu', 'nominate'], ['2010', 'adammo', 'premios clarín', 'best music video of the year', 'argentina', 'nominate'], ['2010', 'adammo', 'premios clarín', 'best international breakthrough', 'argentina', 'nominate'], ['2010', 'adammo', 'premios clarín', 'best international album', 'argentina', 'nominate'], ['2010', 'algún día', 'radio can', 'best video', 'colombia', 'nominate'], ['2011', 'adammo', 'premios apdayc', 'rock group of the year', 'perú', 'winner'], ['2011', 'adammo', 'mtv europe music awards', 'world wide act latin american', 'europa', 'nominate'], ['2011', 'adammo', 'zona joven', 'best pop rock peruano', 'perú', 'winner'], ['2012', 'siento que caigo', 'radio can', 'song of the year', 'perú', 'nominate']]

list of the busiest airports in brazil

https://en.wikipedia.org/wiki/List_of_the_busiest_airports_in_Brazil

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15494883-26.html.csv

comparative

the airport in brasilia saw more total passengers than the airport in salvador .

{'row_1': '3', 'row_2': '6', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'brasília'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to brasília .', 'tostr': 'filter_eq { all_rows ; location ; brasília }'}, 'total passengers'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; brasília } ; total passengers }', 'tointer': 'select the rows whose location record fuzzily matches to brasília . take the total passengers record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'salvador'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to salvador .', 'tostr': 'filter_eq { all_rows ; location ; salvador }'}, 'total passengers'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; location ; salvador } ; total passengers }', 'tointer': 'select the rows whose location record fuzzily matches to salvador . take the total passengers record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; location ; brasília } ; total passengers } ; hop { filter_eq { all_rows ; location ; salvador } ; total passengers } } = true', 'tointer': 'select the rows whose location record fuzzily matches to brasília . take the total passengers record of this row . select the rows whose location record fuzzily matches to salvador . take the total passengers record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; location ; brasília } ; total passengers } ; hop { filter_eq { all_rows ; location ; salvador } ; total passengers } } = true

select the rows whose location record fuzzily matches to brasília . take the total passengers record of this row . select the rows whose location record fuzzily matches to salvador . take the total passengers record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'brasília_8': 8, 'total passengers_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'location_11': 11, 'salvador_12': 12, 'total passengers_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'brasília_8': 'brasília', 'total passengers_9': 'total passengers', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'location_11': 'location', 'salvador_12': 'salvador', 'total passengers_13': 'total passengers'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'location_7': [0], 'brasília_8': [0], 'total passengers_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'location_11': [1], 'salvador_12': [1], 'total passengers_13': [3]}

['rank', 'location', 'total passengers', 'annual change', 'capacity in use']

[['1', 'são paulo', '13611227', '12.8 %', '113.4 %'], ['2', 'são paulo', '12940193', '11.7 %', '78.4 %'], ['3', 'brasília', '9926786', '45.1 %', '134.1 %'], ['4', 'rio de janeiro', '6024930', '30.4 %', '40.2 %'], ['5', 'rio de janeiro', '4887306', '9.2 %', '152.7 %'], ['6', 'salvador', '4145371', '20.0 %', '69.1 %'], ['7', 'porto alegre', '3215545', '11.6 %', '52.7 %'], ['8', 'belo horizonte', '3194715', '7.5 %', '213.0 %'], ['9', 'recife', '3173672', '16.1 %', '63.5 %'], ['10', 'curitiba', '2840349', '13.0 %', '81.2 %'], ['11', 'fortaleza', '2317869', '24.0 %', '77.3 %'], ['12', 'florianópolis', '1382577', '7.8 %', '125.7 %'], ['13', 'manaus', '1368968', '10.3 %', '75.4 %'], ['14', 'belém', '1330965', '13.5 %', '49.3 %'], ['15', 'vitória', '1246222', '6.1 %', '222.5 %']]

2005 games of the small states of europe

https://en.wikipedia.org/wiki/2005_Games_of_the_Small_States_of_Europe

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11149631-1.html.csv

aggregation

at the 2005 games of the small states of europe , the average number of gold medals won was 15 .

{'scope': 'all', 'col': '3', 'type': 'average', 'result': '15', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'gold'], 'result': '15', 'ind': 0, 'tostr': 'avg { all_rows ; gold }'}, '15'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; gold } ; 15 } = true', 'tointer': 'the average of the gold record of all rows is 15 .'}

round_eq { avg { all_rows ; gold } ; 15 } = true

the average of the gold record of all rows is 15 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'gold_4': 4, '15_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '15_5': '15'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'gold_4': [0], '15_5': [1]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'cyprus', '39', '28', '24', '91'], ['2', 'iceland', '26', '23', '27', '76'], ['3', 'luxembourg', '18', '21', '23', '62'], ['4', 'monaco', '11', '8', '18', '37'], ['5', 'andorra', '8', '14', '9', '31'], ['6', 'malta', '7', '13', '18', '38'], ['7', 'san marino', '6', '9', '7', '22'], ['8', 'liechtenstein', '5', '5', '3', '13']]

christian poulsen

https://en.wikipedia.org/wiki/Christian_Poulsen

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1468209-2.html.csv

aggregation

for christian poulsen the total combined score for matches at parken stadium , copenhagen was 7 .

{'scope': 'subset', 'col': '3', 'type': 'sum', 'result': '7', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'parken stadium , copenhagen'}}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'venue', 'parken stadium , copenhagen'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; venue ; parken stadium , copenhagen }', 'tointer': 'select the rows whose venue record fuzzily matches to parken stadium , copenhagen .'}, 'score'], 'result': '7', 'ind': 1, 'tostr': 'sum { filter_eq { all_rows ; venue ; parken stadium , copenhagen } ; score }'}, '7'], 'result': True, 'ind': 2, 'tostr': 'round_eq { sum { filter_eq { all_rows ; venue ; parken stadium , copenhagen } ; score } ; 7 } = true', 'tointer': 'select the rows whose venue record fuzzily matches to parken stadium , copenhagen . the sum of the score record of these rows is 7 .'}

round_eq { sum { filter_eq { all_rows ; venue ; parken stadium , copenhagen } ; score } ; 7 } = true

select the rows whose venue record fuzzily matches to parken stadium , copenhagen . the sum of the score record of these rows is 7 .

3

3

{'eq_2': 2, 'result_3': 3, 'sum_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'venue_5': 5, 'parken stadium, copenhagen_6': 6, 'score_7': 7, '7_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'sum_1': 'sum', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'venue_5': 'venue', 'parken stadium, copenhagen_6': 'parken stadium , copenhagen', 'score_7': 'score', '7_8': '7'}

{'eq_2': [3], 'result_3': [], 'sum_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'venue_5': [0], 'parken stadium, copenhagen_6': [0], 'score_7': [1], '7_8': [2]}

['date', 'venue', 'score', 'result', 'competition']

[['26 march 2005', 'parken stadium , copenhagen', '2 - 0', '3 - 0', '2006 world cup qualification'], ['7 september 2005', 'parken stadium , copenhagen', '2 - 0', '6 - 1', '2006 world cup qualification'], ['29 may 2008', 'philips stadion , eindhoven', '1 - 1', '1 - 1', 'friendly match'], ['10 september 2008', 'estádio josé alvalade , lisbon', '2 - 2', '3 - 2', '2010 world cup qualification'], ['1 april 2009', 'parken stadium , copenhagen', '3 - 0', '3 - 0', '2010 world cup qualification'], ['27 may 2010', 'nordjyske arena , aalborg', '1 - 0', '2 - 0', 'friendly match']]

song - hee kim

https://en.wikipedia.org/wiki/Song-Hee_Kim

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24330912-1.html.csv

comparative

song-hee kim played in more tournaments in her last year golfing ( 2011 ) than in her first year of golfing ( 2007 ) .

{'row_1': '5', 'row_2': '1', 'col': '2', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2011'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose year record fuzzily matches to 2011 .', 'tostr': 'filter_eq { all_rows ; year ; 2011 }'}, 'tournaments played'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; year ; 2011 } ; tournaments played }', 'tointer': 'select the rows whose year record fuzzily matches to 2011 . take the tournaments played record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'year', '2007'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose year record fuzzily matches to 2007 .', 'tostr': 'filter_eq { all_rows ; year ; 2007 }'}, 'tournaments played'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; year ; 2007 } ; tournaments played }', 'tointer': 'select the rows whose year record fuzzily matches to 2007 . take the tournaments played record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; year ; 2011 } ; tournaments played } ; hop { filter_eq { all_rows ; year ; 2007 } ; tournaments played } } = true', 'tointer': 'select the rows whose year record fuzzily matches to 2011 . take the tournaments played record of this row . select the rows whose year record fuzzily matches to 2007 . take the tournaments played record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; year ; 2011 } ; tournaments played } ; hop { filter_eq { all_rows ; year ; 2007 } ; tournaments played } } = true

select the rows whose year record fuzzily matches to 2011 . take the tournaments played record of this row . select the rows whose year record fuzzily matches to 2007 . take the tournaments played record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'year_7': 7, '2011_8': 8, 'tournaments played_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'year_11': 11, '2007_12': 12, 'tournaments played_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'year_7': 'year', '2011_8': '2011', 'tournaments played_9': 'tournaments played', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'year_11': 'year', '2007_12': '2007', 'tournaments played_13': 'tournaments played'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'year_7': [0], '2011_8': [0], 'tournaments played_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'year_11': [1], '2007_12': [1], 'tournaments played_13': [3]}

['year', 'tournaments played', 'cuts made', 'wins', '2nd', '3rd', 'top 10s', 'best finish', 'earnings', 'money list rank', 'scoring average', 'scoring rank']

[['2007', '19', '10', '0', '0', '0', '0', 't22', '78660', '99', '73.72', '75'], ['2008', '25', '21', '0', '2', '1', '7', '2', '980883', '14', '71.23', '10'], ['2009', '25', '23', '0', '0', '2', '12', 't3', '1032031', '11', '70.52', '8'], ['2010', '22', '22', '0', '2', '3', '15', '2', '1208698', '8', '70.21', '4'], ['2011', '22', '19', '0', '1', '0', '2', '2', '350376', '33', '72.62', '47']]

1985 buffalo bills season

https://en.wikipedia.org/wiki/1985_Buffalo_Bills_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17383560-1.html.csv

ordinal

of the defensive backs picked by the buffalo bills , glenn jones was the player with the highest pick number .

{'scope': 'subset', 'row': '13', 'col': '2', 'order': '1', 'col_other': '3', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'subset': {'col': '4', 'criterion': 'equal', 'value': 'defensive back'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'defensive back'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; position ; defensive back }', 'tointer': 'select the rows whose position record fuzzily matches to defensive back .'}, 'pick', '1'], 'result': None, 'ind': 1, 'tostr': 'nth_argmax { filter_eq { all_rows ; position ; defensive back } ; pick ; 1 }'}, 'player'], 'result': 'glenn jones', 'ind': 2, 'tostr': 'hop { nth_argmax { filter_eq { all_rows ; position ; defensive back } ; pick ; 1 } ; player }'}, 'glenn jones'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { nth_argmax { filter_eq { all_rows ; position ; defensive back } ; pick ; 1 } ; player } ; glenn jones } = true', 'tointer': 'select the rows whose position record fuzzily matches to defensive back . select the row whose pick record of these rows is 1st maximum . the player record of this row is glenn jones .'}

eq { hop { nth_argmax { filter_eq { all_rows ; position ; defensive back } ; pick ; 1 } ; player } ; glenn jones } = true

select the rows whose position record fuzzily matches to defensive back . select the row whose pick record of these rows is 1st maximum . the player record of this row is glenn jones .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'nth_argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'position_6': 6, 'defensive back_7': 7, 'pick_8': 8, '1_9': 9, 'player_10': 10, 'glenn jones_11': 11}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'nth_argmax_1': 'nth_argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'position_6': 'position', 'defensive back_7': 'defensive back', 'pick_8': 'pick', '1_9': '1', 'player_10': 'player', 'glenn jones_11': 'glenn jones'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'nth_argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'position_6': [0], 'defensive back_7': [0], 'pick_8': [1], '1_9': [1], 'player_10': [2], 'glenn jones_11': [3]}

['round', 'pick', 'player', 'position', 'school / club team']

[['1', '1', 'bruce smith', 'defensive end', 'virginia tech'], ['1', '14', 'derrick burroughs', 'defensive back', 'memphis'], ['2', '29', 'mark traynowicz', 'guard', 'nebraska'], ['2', '42', 'chris burkett', 'wide receiver', 'jackson state'], ['3', '57', 'frank reich', 'quarterback', 'maryland'], ['3', '63', 'hal garner', 'linebacker', 'utah state'], ['4', '86', 'andre reed', 'wide receiver', 'kutztown state'], ['4', '112', 'dale hellestrae', 'tackle', 'southern methodist'], ['5', '130', 'jimmy teal', 'wide receiver', 'texas a & m'], ['6', '141', 'mike hamby', 'defensive end', 'utah state'], ['7', '169', 'ron pitts', 'defensive back', 'ucla'], ['8', '197', 'jacque robinson', 'fullback', 'washington'], ['9', '225', 'glenn jones', 'defensive back', 'norfolk state'], ['10', '253', 'chris babyar', 'guard', 'illinois'], ['11', '282', 'james seawright', 'linebacker', 'south carolina'], ['12', '333', 'paul woodside', 'kicker', 'west virginia']]

george mason patriots men 's basketball

https://en.wikipedia.org/wiki/George_Mason_Patriots_men%27s_basketball

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12661367-1.html.csv

superlative

carlos yates scored the highest amount of points of the george mason patriots men 's basketball players .

{'scope': 'all', 'col_superlative': '6', 'row_superlative': '1', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'total points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; total points }'}, 'player'], 'result': 'carlos yates', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; total points } ; player }'}, 'carlos yates'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; total points } ; player } ; carlos yates } = true', 'tointer': 'select the row whose total points record of all rows is maximum . the player record of this row is carlos yates .'}

eq { hop { argmax { all_rows ; total points } ; player } ; carlos yates } = true

select the row whose total points record of all rows is maximum . the player record of this row is carlos yates .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'total points_5': 5, 'player_6': 6, 'carlos yates_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'total points_5': 'total points', 'player_6': 'player', 'carlos yates_7': 'carlos yates'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'total points_5': [0], 'player_6': [1], 'carlos yates_7': [2]}

['rank', 'player', 'years', 'games', 'ppg avg', 'total points']

[['1', 'carlos yates', '1981 - 1985', '109', '22.2', '2420'], ['2', 'kenny sanders', '1985 - 1989', '107', '20.3', '2177'], ['3', 'george evans', '1997 - 2001', '116', '16.8', '1953'], ['4', 'robert dykes', '1987 - 1991', '122', '13.4', '1642'], ['5', 'ryan pearson', '2008 - 2012', '129', '12.6', '1626'], ['6', 'andre gaddy', '1977 - 1982', '98', '16.0', '1568'], ['7', 'rob rose', '1982 - 1986', '113', '13.8', '1565'], ['8', 'will thomas', '2004 - 2008', '131', '11.9', '1564'], ['9', 'folarin campbell', '2004 - 2008', '130', '11.9', '1545'], ['10', 'rudolph jones', '1971 - 1973', '59', '25.8', '1525']]

claus jensen

https://en.wikipedia.org/wiki/Claus_Jensen

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054921-2.html.csv

superlative

the competition of claus jensen 's with the latest date was in copenhagen , denmark .

{'scope': 'all', 'col_superlative': '1', 'row_superlative': '8', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'date'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; date }'}, 'date'], 'result': '7 september 2005', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; date } ; date }'}, '7 september 2005'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; date } ; date } ; 7 september 2005 } = true', 'tointer': 'select the row whose date record of all rows is maximum . the date record of this row is 7 september 2005 .'}

eq { hop { argmax { all_rows ; date } ; date } ; 7 september 2005 } = true

select the row whose date record of all rows is maximum . the date record of this row is 7 september 2005 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'date_5': 5, 'date_6': 6, '7 september 2005_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'date_5': 'date', 'date_6': 'date', '7 september 2005_7': '7 september 2005'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'date_5': [0], 'date_6': [1], '7 september 2005_7': [2]}

['date', 'venue', 'score', 'result', 'competition']

[['24 march 2001', 'valletta , malta', '4 - 0', '5 - 0', '2002 world cup qualification'], ['12 february 2003', 'cairo , egypt', '1 - 1', '4 - 1', 'friendly match'], ['12 february 2003', 'cairo , egypt', '3 - 1', '4 - 1', 'friendly match'], ['12 february 2003', 'cairo , egypt', '4 - 1', '4 - 1', 'friendly match'], ['11 june 2003', 'luxembourg , luxembourg', '1 - 0', '2 - 0', 'euro 2004 qualification'], ['18 august 2004', 'poznan , poland', '4 - 1', '5 - 1', 'friendly match'], ['3 september 2005', 'istanbul , turkey', '1 - 0', '2 - 2', '2006 world cup qualification'], ['7 september 2005', 'copenhagen , denmark', '1 - 0', '6 - 1', '2006 world cup qualification']]

iran at the asian games

https://en.wikipedia.org/wiki/Iran_at_the_Asian_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10882501-1.html.csv

comparative

iran won more total medals in 1958 than in 1966 .

{'row_1': '3', 'row_2': '5', 'col': '5', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'games', '1958 tokyo'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose games record fuzzily matches to 1958 tokyo .', 'tostr': 'filter_eq { all_rows ; games ; 1958 tokyo }'}, 'total'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; games ; 1958 tokyo } ; total }', 'tointer': 'select the rows whose games record fuzzily matches to 1958 tokyo . take the total record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'games', '1966 bangkok'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose games record fuzzily matches to 1966 bangkok .', 'tostr': 'filter_eq { all_rows ; games ; 1966 bangkok }'}, 'total'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; games ; 1966 bangkok } ; total }', 'tointer': 'select the rows whose games record fuzzily matches to 1966 bangkok . take the total record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; games ; 1958 tokyo } ; total } ; hop { filter_eq { all_rows ; games ; 1966 bangkok } ; total } } = true', 'tointer': 'select the rows whose games record fuzzily matches to 1958 tokyo . take the total record of this row . select the rows whose games record fuzzily matches to 1966 bangkok . take the total record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; games ; 1958 tokyo } ; total } ; hop { filter_eq { all_rows ; games ; 1966 bangkok } ; total } } = true

select the rows whose games record fuzzily matches to 1958 tokyo . take the total record of this row . select the rows whose games record fuzzily matches to 1966 bangkok . take the total record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'games_7': 7, '1958 tokyo_8': 8, 'total_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'games_11': 11, '1966 bangkok_12': 12, 'total_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'games_7': 'games', '1958 tokyo_8': '1958 tokyo', 'total_9': 'total', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'games_11': 'games', '1966 bangkok_12': '1966 bangkok', 'total_13': 'total'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'games_7': [0], '1958 tokyo_8': [0], 'total_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'games_11': [1], '1966 bangkok_12': [1], 'total_13': [3]}

['games', 'gold', 'silver', 'bronze', 'total', 'rank']

[['1951 new delhi', '8', '6', '2', '16', '3'], ['1954 manila', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1958 tokyo', '7', '14', '11', '32', '4'], ['1962 jakarta', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1966 bangkok', '6', '8', '17', '31', '6'], ['1970 bangkok', '9', '7', '7', '23', '4'], ['1974 tehran', '36', '28', '17', '81', '2'], ['1978 bangkok', 'did not participate', 'did not participate', 'did not participate', 'did not participate', 'did not participate'], ['1982 new delhi', '4', '4', '4', '12', '7'], ['1986 seoul', '6', '6', '10', '22', '4'], ['1990 beijing', '4', '6', '8', '18', '5'], ['1994 hiroshima', '9', '9', '8', '26', '6'], ['1998 bangkok', '10', '11', '13', '34', '7'], ['2002 busan', '8', '14', '14', '36', '10'], ['2006 doha', '11', '15', '22', '48', '6'], ['2010 guangzhou', '20', '15', '24', '59', '4'], ['total', '138', '143', '157', '438', '4']]

duchess of nemours

https://en.wikipedia.org/wiki/Duchess_of_Nemours

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1825009-5.html.csv

comparative

of the women to gain the title ' duchess of nemoirs ' on their marriage , margravine johanna of baden-baden gained the title before victoria of saxe-coburg and gotha .

{'row_1': '3', 'row_2': '7', 'col': '4', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'margravine johanna of baden - baden'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to margravine johanna of baden - baden .', 'tostr': 'filter_eq { all_rows ; name ; margravine johanna of baden - baden }'}, 'became duchess'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; margravine johanna of baden - baden } ; became duchess }', 'tointer': 'select the rows whose name record fuzzily matches to margravine johanna of baden - baden . take the became duchess record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'victoria of saxe - coburg and gotha'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to victoria of saxe - coburg and gotha .', 'tostr': 'filter_eq { all_rows ; name ; victoria of saxe - coburg and gotha }'}, 'became duchess'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; victoria of saxe - coburg and gotha } ; became duchess }', 'tointer': 'select the rows whose name record fuzzily matches to victoria of saxe - coburg and gotha . take the became duchess record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; name ; margravine johanna of baden - baden } ; became duchess } ; hop { filter_eq { all_rows ; name ; victoria of saxe - coburg and gotha } ; became duchess } } = true', 'tointer': 'select the rows whose name record fuzzily matches to margravine johanna of baden - baden . take the became duchess record of this row . select the rows whose name record fuzzily matches to victoria of saxe - coburg and gotha . take the became duchess record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; name ; margravine johanna of baden - baden } ; became duchess } ; hop { filter_eq { all_rows ; name ; victoria of saxe - coburg and gotha } ; became duchess } } = true

select the rows whose name record fuzzily matches to margravine johanna of baden - baden . take the became duchess record of this row . select the rows whose name record fuzzily matches to victoria of saxe - coburg and gotha . take the became duchess record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'margravine johanna of baden - baden_8': 8, 'became duchess_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'victoria of saxe - coburg and gotha_12': 12, 'became duchess_13': 13}

{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'margravine johanna of baden - baden_8': 'margravine johanna of baden - baden', 'became duchess_9': 'became duchess', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'victoria of saxe - coburg and gotha_12': 'victoria of saxe - coburg and gotha', 'became duchess_13': 'became duchess'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'margravine johanna of baden - baden_8': [0], 'became duchess_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'victoria of saxe - coburg and gotha_12': [1], 'became duchess_13': [3]}

['name', 'birth', 'marriage', 'became duchess', 'ceased to be duchess', 'death', 'spouse']

[['elizabeth charlotte of the palatinate', '27 may 1652', '16 november 1671', '1672 peerage awarded to husband', "9 june 1701 husband 's death", '9 december 1722', 'philippe , duke of orléans'], ['françoise marie de bourbon , légitimée de france', '25 may 1677', '18 february 1692', "9 june 1701 husband 's accession", "2 december 1723 husband 's death", '1 february 1749', 'philippe , duke of orléans'], ['margravine johanna of baden - baden', '10 november 1704', '13 july 1724', '13 july 1724', '8 july 1726', '8 july 1726', 'louis , duke of orléans'], ['louise henriette de bourbon', '20 june 1726', '17 december 1743', "4 february 1752 husband 's accession", '9 february 1759', '9 february 1759', 'louis philippe , duke of orléans'], ['louise marie adélaïde de bourbon', '13 march 1753', '8 may 1768', "18 november 1785 husband 's accession", "6 november 1793 husband 's execution", '23 june 1821', 'philippe , duke of orléans'], ['maria amalia of naples and sicily', '26 april 1782', '25 november 1809', '25 november 1809', '9 august 1830 became queen consort', '24 march 1866', 'louis philippe i'], ['victoria of saxe - coburg and gotha', '14 february 1822', '27 april 1840', '27 april 1840', '10 december 1857', '10 december 1857', 'prince louis'], ['name', 'birth', 'marriage', 'became duchess', 'ceased to be duchess', 'death', 'spouse']]

1993 - 94 belarusian premier league

https://en.wikipedia.org/wiki/1993%E2%80%9394_Belarusian_Premier_League

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14744886-1.html.csv

superlative

in the 1993 - 94 belarusian premier league , the venue with the highest capacity was minsk at 41040 .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '1', 'value_mentioned': 'yes', 'max_or_min': 'max', 'other_col': '1', 'subset': None}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'max', 'args': ['all_rows', 'capacity'], 'result': '41040', 'ind': 0, 'tostr': 'max { all_rows ; capacity }', 'tointer': 'the maximum capacity record of all rows is 41040 .'}, '41040'], 'result': True, 'ind': 1, 'tostr': 'eq { max { all_rows ; capacity } ; 41040 }', 'tointer': 'the maximum capacity record of all rows is 41040 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'capacity'], 'result': None, 'ind': 2, 'tostr': 'argmax { all_rows ; capacity }'}, 'team'], 'result': 'dinamo minsk', 'ind': 3, 'tostr': 'hop { argmax { all_rows ; capacity } ; team }'}, 'dinamo minsk'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; team } ; dinamo minsk }', 'tointer': 'the team record of the row with superlative capacity record is dinamo minsk .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { max { all_rows ; capacity } ; 41040 } ; eq { hop { argmax { all_rows ; capacity } ; team } ; dinamo minsk } } = true', 'tointer': 'the maximum capacity record of all rows is 41040 . the team record of the row with superlative capacity record is dinamo minsk .'}

and { eq { max { all_rows ; capacity } ; 41040 } ; eq { hop { argmax { all_rows ; capacity } ; team } ; dinamo minsk } } = true

the maximum capacity record of all rows is 41040 . the team record of the row with superlative capacity record is dinamo minsk .

6

6

{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'max_0': 0, 'all_rows_7': 7, 'capacity_8': 8, '41040_9': 9, 'str_eq_4': 4, 'str_hop_3': 3, 'argmax_2': 2, 'all_rows_10': 10, 'capacity_11': 11, 'team_12': 12, 'dinamo minsk_13': 13}

{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'max_0': 'max', 'all_rows_7': 'all_rows', 'capacity_8': 'capacity', '41040_9': '41040', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'argmax_2': 'argmax', 'all_rows_10': 'all_rows', 'capacity_11': 'capacity', 'team_12': 'team', 'dinamo minsk_13': 'dinamo minsk'}

{'and_5': [6], 'result_6': [], 'eq_1': [5], 'max_0': [1], 'all_rows_7': [0], 'capacity_8': [0], '41040_9': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'argmax_2': [3], 'all_rows_10': [2], 'capacity_11': [2], 'team_12': [3], 'dinamo minsk_13': [4]}

['team', 'location', 'venue', 'capacity', 'position in 199293']

[['dinamo minsk', 'minsk', 'dinamo , minsk', '41040', '1'], ['kim', 'vitebsk', 'central , vitebsk', '8300', '2'], ['dinamo - 93', 'minsk', 'dinamo , minsk', '41040', '3'], ['neman', 'grodno', 'neman', '6300', '4'], ['dnepr', 'mogilev', 'spartak , mogilev', '11200', '5'], ['fandok', 'bobruisk', 'spartak , bobruisk', '3550', '6'], ['dinamo brest', 'brest', 'dinamo , brest', '10080', '7'], ['torpedo mogilev', 'mogilev', 'torpedo , mogilev', '3500', '8'], ['torpedo minsk', 'minsk', 'torpedo , minsk', '5200', '9'], ['gomselmash', 'gomel', 'central , gomel', '11800', '10'], ['shakhtyor', 'soligorsk', 'stroitel', '5000', '11'], ['lokomotiv', 'vitebsk', 'central , vitebsk', '8300', '12'], ['molodechno', 'molodechno', 'city stadium', '5500', '13'], ['stroitel', 'starye dorogi', 'stroitel', '2000', '14'], ['vedrich', 'rechytsa', 'central , rechytsa', '3550', '15'], ['shinnik', 'bobruisk', 'spartak , bobruisk', '3550', 'first league , 1']]

list of vehicle speed records

https://en.wikipedia.org/wiki/List_of_vehicle_speed_records

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16343705-3.html.csv

comparative

the helicopter speed record was achieved earlier than the glider ( sailplane ) record .

{'row_1': '5', 'row_2': '6', 'col': '6', 'col_other': '1', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'helicopter'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose category record fuzzily matches to helicopter .', 'tostr': 'filter_eq { all_rows ; category ; helicopter }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; category ; helicopter } ; date }', 'tointer': 'select the rows whose category record fuzzily matches to helicopter . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'category', 'glider ( sailplane )'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose category record fuzzily matches to glider ( sailplane ) .', 'tostr': 'filter_eq { all_rows ; category ; glider ( sailplane ) }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; category ; glider ( sailplane ) } ; date }', 'tointer': 'select the rows whose category record fuzzily matches to glider ( sailplane ) . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; category ; helicopter } ; date } ; hop { filter_eq { all_rows ; category ; glider ( sailplane ) } ; date } } = true', 'tointer': 'select the rows whose category record fuzzily matches to helicopter . take the date record of this row . select the rows whose category record fuzzily matches to glider ( sailplane ) . take the date record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; category ; helicopter } ; date } ; hop { filter_eq { all_rows ; category ; glider ( sailplane ) } ; date } } = true

select the rows whose category record fuzzily matches to helicopter . take the date record of this row . select the rows whose category record fuzzily matches to glider ( sailplane ) . take the date record of this row . the first record is less than the second record .

5

5

{'less_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'category_7': 7, 'helicopter_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'category_11': 11, 'glider (sailplane)_12': 12, 'date_13': 13}

{'less_4': 'less', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'category_7': 'category', 'helicopter_8': 'helicopter', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'category_11': 'category', 'glider (sailplane)_12': 'glider ( sailplane )', 'date_13': 'date'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'category_7': [0], 'helicopter_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'category_11': [1], 'glider (sailplane)_12': [1], 'date_13': [3]}

['category', 'speed ( km / h )', 'speed ( mph )', 'vehicle', 'pilot', 'date']

[['rocket - powered aircraft', '7258', '4510', 'north american x - 15', 'william j knight', '3 oct 1967'], ['manned air - breathing craft', '3530', '2194', 'lockheed sr - 71 blackbird', 'eldon w joersz', '28 jul 1976'], ['propeller - driven aircraft', '870', '541', 'tupolev tu - 114', 'ivan soukhomline', '00 jan 1960'], ['piston - engined propeller - driven aircraft', '850.1', '528.33', 'grumman f8f bearcat rare bear ( n777l )', 'lyle shelton', '21 aug 1989'], ['helicopter', '401.0', '249.1', 'westland lynx 800 g - lynx', 'john egginton', '11 aug 1986'], ['glider ( sailplane )', '306.8', '190.6', 'schempp - hirth nimbus - 4dm', 'klaus ohlmann and matias garcia mazzaro', '22 dec 2006'], ['human - powered aircraft', '32', '19.8', 'mit monarch b', 'frank scarabino', '1 may 1984']]

burn notice ( season 4 )

https://en.wikipedia.org/wiki/Burn_Notice_%28season_4%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26845668-1.html.csv

majority

the majority of the burn notice season 4 episodes had a viewership of 5 million of more .

{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '5', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'us viewers ( millions )', '5'], 'result': True, 'ind': 0, 'tointer': 'for the us viewers ( millions ) records of all rows , most of them are greater than 5 .', 'tostr': 'most_greater { all_rows ; us viewers ( millions ) ; 5 } = true'}

most_greater { all_rows ; us viewers ( millions ) ; 5 } = true

for the us viewers ( millions ) records of all rows , most of them are greater than 5 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'us viewers (millions)_3': 3, '5_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'us viewers (millions)_3': 'us viewers ( millions )', '5_4': '5'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'us viewers (millions)_3': [0], '5_4': [0]}

['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'production code', 'us viewers ( millions )']

[['45', '1', 'friends and enemies', 'tim matheson', 'matt nix', 'june 3 , 2010', 'bn401', '6.62'], ['46', '2', 'fast friends', 'dennie gordon', 'rashad raisani', 'june 10 , 2010', 'bn402', '5.67'], ['47', '3', 'made man', 'jeffrey donovan', 'alfredo barrios , jr', 'june 17 , 2010', 'bn403', '5.31'], ['48', '4', 'breach of faith', 'jeremiah chechik', 'ben watkins', 'june 24 , 2010', 'bn404', '5.33'], ['49', '5', 'neighborhood watch', 'kevin bray', 'michael horowitz', 'july 1 , 2010', 'bn405', '5.21'], ['50', '6', 'entry point', 'jeffrey hunt', "craig o'neill", 'july 15 , 2010', 'bn406', '5.65'], ['51', '7', 'past & future tense', 'jeremiah chechik', 'jason tracey', 'july 22 , 2010', 'bn407', '5.87'], ['52', '8', "where there 's smoke", 'kevin bray', 'lisa joy', 'july 29 , 2010', 'bn408', '5.38'], ['53', '9', 'center of the storm', 'colin bucksey', 'ryan johnson & peter lalayanis', 'august 5 , 2010', 'bn409', '5.69'], ['54', '10', 'hard time', 'dennie gordon', 'alfredo barrios , jr', 'august 12 , 2010', 'bn410', '5.57'], ['55', '11', 'blind spot', 'michael smith', 'michael horowitz', 'august 19 , 2010', 'bn411', '5.50'], ['56', '12', 'guilty as charged', 'jeremiah chechik', 'matt nix', 'august 26 , 2010', 'bn412', '6.29'], ['57', '13', 'eyes open', 'dennie gordon', 'jason tracey', 'november 11 , 2010', 'bn413', '4.32'], ['58', '14', 'hot property', 'jonathan frakes', 'rashad raisani', 'november 18 , 2010', 'bn414', '3.50'], ['59', '15', 'brotherly love', 'terry miller', 'ben watkins', 'december 2 , 2010', 'bn415', '3.70'], ['60', '16', 'dead or alive', 'peter markle', 'lisa joy', 'december 9 , 2010', 'bn416', '4.34'], ['61', '17', 'out of the fire', 'marc roskin', "craig o'neill", 'december 16 , 2010', 'bn417', '4.77']]

1979 cincinnati bengals season

https://en.wikipedia.org/wiki/1979_Cincinnati_Bengals_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17643197-2.html.csv

majority

the majority of games in the 1979 cincinnati bengals season resulted in losses for the bengals .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'fuzzily_match', 'value': 'l', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'result', 'l'], 'result': True, 'ind': 0, 'tointer': 'for the result records of all rows , most of them fuzzily match to l .', 'tostr': 'most_eq { all_rows ; result ; l } = true'}

most_eq { all_rows ; result ; l } = true

for the result records of all rows , most of them fuzzily match to l .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'result_3': 3, 'l_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'result_3': 'result', 'l_4': 'l'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'result_3': [0], 'l_4': [0]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 2 , 1979', 'denver broncos', 'l 10 - 0', '74788'], ['2', 'september 9 , 1979', 'buffalo bills', 'l 51 - 24', '43504'], ['3', 'september 16 , 1979', 'new england patriots', 'l 20 - 14', '41805'], ['4', 'september 23 , 1979', 'houston oilers', 'l 30 - 27', '45615'], ['5', 'september 30 , 1979', 'dallas cowboys', 'l 38 - 13', '63179'], ['6', 'october 7 , 1979', 'kansas city chiefs', 'l 10 - 7', '40041'], ['7', 'october 14 , 1979', 'pittsburgh steelers', 'w 34 - 10', '52381'], ['8', 'october 21 , 1979', 'cleveland browns', 'l 28 - 27', '75119'], ['9', 'october 28 , 1979', 'philadelphia eagles', 'w 37 - 13', '42036'], ['10', 'november 4 , 1979', 'baltimore colts', 'l 38 - 28', '37740'], ['11', 'november 11 , 1979', 'san diego chargers', 'l 26 - 24', '40782'], ['12', 'november 18 , 1979', 'houston oilers', 'l 42 - 21', '49829'], ['13', 'november 25 , 1979', 'st louis cardinals', 'w 34 - 28', '25103'], ['14', 'december 2 , 1979', 'pittsburgh steelers', 'l 37 - 17', '46521'], ['15', 'december 9 , 1979', 'washington redskins', 'l 28 - 14', '52882'], ['16', 'december 16 , 1979', 'cleveland browns', 'w 16 - 12', '42183']]

2008 - 09 nbl season

https://en.wikipedia.org/wiki/2008%E2%80%9309_NBL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16653153-13.html.csv

comparative

the home and away teams from both games scores more points on the october 22 games than on the october 24th game .

{'row_1': '1', 'row_2': '3', 'col': '3', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '22 october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to 22 october .', 'tostr': 'filter_eq { all_rows ; date ; 22 october }'}, 'score'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; 22 october } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 22 october . take the score record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '24 october'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to 24 october .', 'tostr': 'filter_eq { all_rows ; date ; 24 october }'}, 'score'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; 24 october } ; score }', 'tointer': 'select the rows whose date record fuzzily matches to 24 october . take the score record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; 22 october } ; score } ; hop { filter_eq { all_rows ; date ; 24 october } ; score } } = true', 'tointer': 'select the rows whose date record fuzzily matches to 22 october . take the score record of this row . select the rows whose date record fuzzily matches to 24 october . take the score record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; date ; 22 october } ; score } ; hop { filter_eq { all_rows ; date ; 24 october } ; score } } = true

select the rows whose date record fuzzily matches to 22 october . take the score record of this row . select the rows whose date record fuzzily matches to 24 october . take the score record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'date_7': 7, '22 october_8': 8, 'score_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, '24 october_12': 12, 'score_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'date_7': 'date', '22 october_8': '22 october', 'score_9': 'score', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', '24 october_12': '24 october', 'score_13': 'score'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], '22 october_8': [0], 'score_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], '24 october_12': [1], 'score_13': [3]}

['date', 'home team', 'score', 'away team', 'venue', 'box score', 'report']

[['22 october', 'townsville crocodiles', '103 - 101', 'sydney spirit', 'townsville entertainment centre', 'box score', '-'], ['22 october', 'cairns taipans', '101 - 92', 'new zealand breakers', 'cairns convention centre', 'box score', '-'], ['24 october', 'wollongong hawks', '98 - 96', 'gold coast blaze', 'win entertainment centre', 'box score', '-'], ['25 october', 'adelaide 36ers', '93 - 104', 'perth wildcats', 'distinctive homes dome', 'box score', '-'], ['25 october', 'gold coast blaze', '113 - 116', 'new zealand breakers', 'gold coast convention centre', 'box score', '-'], ['25 october', 'melbourne tigers', '110 - 97', 'townsville crocodiles', 'state netball and hockey centre', 'box score', '-'], ['25 october', 'south dragons', '94 - 65', 'cairns taipans', 'hisense arena', 'box score', '-'], ['26 october', 'sydney spirit', '99 - 86', 'wollongong hawks', 'state sports centre', 'box score', '-']]

visa requirements for croatian citizens

https://en.wikipedia.org/wiki/Visa_requirements_for_Croatian_citizens

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25965003-3.html.csv

count

three of the countries have an unlimited length of stay .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'unlimited', 'result': '3', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'length of stay permitted', 'unlimited'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose length of stay permitted record fuzzily matches to unlimited .', 'tostr': 'filter_eq { all_rows ; length of stay permitted ; unlimited }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; length of stay permitted ; unlimited } }', 'tointer': 'select the rows whose length of stay permitted record fuzzily matches to unlimited . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; length of stay permitted ; unlimited } } ; 3 } = true', 'tointer': 'select the rows whose length of stay permitted record fuzzily matches to unlimited . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; length of stay permitted ; unlimited } } ; 3 } = true

select the rows whose length of stay permitted record fuzzily matches to unlimited . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'length of stay permitted_5': 5, 'unlimited_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'length of stay permitted_5': 'length of stay permitted', 'unlimited_6': 'unlimited', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'length of stay permitted_5': [0], 'unlimited_6': [0], '3_7': [2]}

['countries and territories', 'conditions of access', 'length of stay permitted', 'fee ( if applicable )', 'access using a croatian identity card']

[['european union', 'visa - free', 'freedom of movement', 'n / a', 'yes'], ['albania', 'visa - free', '90 days', 'n / a', 'yes'], ['andorra', 'visa - free', '90 days', 'n / a', 'yes'], ['bosnia and herzegovina', 'visa - free', '90 days', 'n / a', 'yes'], ['faroe islands', 'visa - free', '90 days', 'n / a', 'yes'], ['guernsey', 'visa - free', 'unlimited access', 'n / a', 'yes'], ['iceland', 'visa - free', 'freedom of movement', 'n / a', 'passport required'], ['isle of man', 'visa - free', 'unlimited access', 'n / a', 'yes'], ['jersey', 'visa - free', 'unlimited access', 'n / a', 'yes'], ['kosovo', 'visa - free', '90 days', 'n / a', 'yes'], ['liechtenstein', 'visa - free', 'freedom of movement', 'n / a', 'yes'], ['monaco', 'visa - free', '90 days', 'n / a', 'yes'], ['macedonia', 'visa - free', '90 days', 'n / a', 'yes'], ['moldova', 'visa - free', '90 days', 'n / a', 'passport required'], ['montenegro', 'visa - free', '90 days', 'n / a', 'yes'], ['norway', 'visa - free', 'freedom of movement', 'n / a', 'passport required'], ['san marino', 'visa - free', '90 days', 'n / a', 'yes'], ['serbia', 'visa - free', '90 days', 'n / a', 'yes'], ['switzerland', 'visa - free', 'freedom of movement', 'n / a', 'passport required'], ['ukraine', 'visa - free', '90 days', 'n / a', 'passport required']]

1937 in brazilian football

https://en.wikipedia.org/wiki/1937_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15352382-1.html.csv

count

there were two teams with just one draw in the 1937 brazilian football league .

{'scope': 'all', 'criterion': 'equal', 'value': '1', 'result': '2', 'col': '6', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'drawn', '1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose drawn record is equal to 1 .', 'tostr': 'filter_eq { all_rows ; drawn ; 1 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; drawn ; 1 } }', 'tointer': 'select the rows whose drawn record is equal to 1 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; drawn ; 1 } } ; 2 } = true', 'tointer': 'select the rows whose drawn record is equal to 1 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; drawn ; 1 } } ; 2 } = true

select the rows whose drawn record is equal to 1 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'drawn_5': 5, '1_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'drawn_5': 'drawn', '1_6': '1', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'drawn_5': [0], '1_6': [0], '2_7': [2]}

['position', 'team', 'points', 'played', 'won', 'drawn', 'lost', 'for', 'against', 'difference']

[['1', 'corinthians', '22', '14', '10', '2', '2', '33', '14', '19'], ['2', 'palestra itã ¡ lia - sp', '21', '14', '10', '1', '3', '35', '12', '23'], ['3', 'portuguesa santista', '19', '14', '8', '3', '3', '27', '18', '9'], ['4', 'estudantes paulista', '15', '14', '7', '1', '6', '33', '22', '11'], ['5', 'santos', '14', '14', '5', '4', '5', '27', '20', '7']]

miss mundo dominicana 2006

https://en.wikipedia.org/wiki/Miss_Mundo_Dominicana_2006

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-22447251-2.html.csv

unique

of the miss mundo contestants whose hometown was santiago de los caballeros , only valerie chardonnens vargas was under 19 years old .

{'scope': 'subset', 'row': '9', 'col': '3', 'col_other': '2', 'criterion': 'less_than', 'value': '19', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'santiago de los caballeros'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'hometown', 'santiago de los caballeros'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; hometown ; santiago de los caballeros }', 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros .'}, 'age', '19'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros . among these rows , select the rows whose age record is less than 19 .', 'tostr': 'filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } }', 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros . among these rows , select the rows whose age record is less than 19 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_less', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'hometown', 'santiago de los caballeros'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; hometown ; santiago de los caballeros }', 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros .'}, 'age', '19'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros . among these rows , select the rows whose age record is less than 19 .', 'tostr': 'filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 }'}, 'contestant'], 'result': 'valerie chardonnens vargas', 'ind': 3, 'tostr': 'hop { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } ; contestant }'}, 'valerie chardonnens vargas'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } ; contestant } ; valerie chardonnens vargas }', 'tointer': 'the contestant record of this unqiue row is valerie chardonnens vargas .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } } ; eq { hop { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } ; contestant } ; valerie chardonnens vargas } } = true', 'tointer': 'select the rows whose hometown record fuzzily matches to santiago de los caballeros . among these rows , select the rows whose age record is less than 19 . there is only one such row in the table . the contestant record of this unqiue row is valerie chardonnens vargas .'}

and { only { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } } ; eq { hop { filter_less { filter_eq { all_rows ; hometown ; santiago de los caballeros } ; age ; 19 } ; contestant } ; valerie chardonnens vargas } } = true

select the rows whose hometown record fuzzily matches to santiago de los caballeros . among these rows , select the rows whose age record is less than 19 . there is only one such row in the table . the contestant record of this unqiue row is valerie chardonnens vargas .

8

6

{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_less_1': 1, 'filter_str_eq_0': 0, 'all_rows_7': 7, 'hometown_8': 8, 'santiago de los caballeros_9': 9, 'age_10': 10, '19_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'contestant_12': 12, 'valerie chardonnens vargas_13': 13}

{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_less_1': 'filter_less', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_7': 'all_rows', 'hometown_8': 'hometown', 'santiago de los caballeros_9': 'santiago de los caballeros', 'age_10': 'age', '19_11': '19', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'contestant_12': 'contestant', 'valerie chardonnens vargas_13': 'valerie chardonnens vargas'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_less_1': [2, 3], 'filter_str_eq_0': [1], 'all_rows_7': [0], 'hometown_8': [0], 'santiago de los caballeros_9': [0], 'age_10': [1], '19_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'contestant_12': [3], 'valerie chardonnens vargas_13': [4]}

['province , community', 'contestant', 'age', 'height', 'hometown', 'geographical regions']

[['azua', 'aurys sánchez tejada', '20', '1.80', 'santo domingo', 'sur'], ['barahona', 'laura sadhalá roman', '19', '1.77', 'santiago de los caballeros', 'sur'], ['com dom miami', 'cristal de moya vargas', '22', '1.73', 'miami', 'exterior'], ['com dom nueva jersey', 'sandra elisabeth tavares valle', '18', '1.83', 'newark', 'exterior'], ['com dom nueva york', 'yamilka massiel santana colón', '18', '1.74', 'the bronx', 'exterior'], ['com dom orlando', 'berkelin rosario castellanos', '23', '1.79', 'orlando', 'exterior'], ['dajabón', 'indhira díaz acosta', '20', '1.76', 'loma de cabrera', 'el cibao'], ['distrito nacional', 'jennifer pérez de la cruz', '20', '1.79', 'santo domingo', 'sur'], ['santiago', 'valerie chardonnens vargas', '18', '1.81', 'santiago de los caballeros', 'el cibao'], ['la romana', 'tania yolanda medina collado', '24', '1.68', 'la romana', 'sur'], ['la vega', 'sarah cristina portes carillo', '22', '1.73', 'constanza', 'el cibao'], ['monte plata', 'zadia núñez de la cruz', '25', '1.75', 'villa bisonó', 'sur'], ['puerto plata', 'ana carolina viñas machado', '21', '1.83', 'santiago de los caballeros', 'el cibao'], ['santiago', 'paola maría torres cohén', '21', '1.73', 'santiago de los caballeros', 'el cibao'], ['santo domingo', 'alexandra díaz bello', '22', '1.78', 'santo domingo', 'sur']]

fai world grand prix 2008

https://en.wikipedia.org/wiki/FAI_World_Grand_Prix_2008

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17277703-7.html.csv

ordinal

uli schwenk recorded the 2nd highest speed in the 2008 fai world grand prix .

{'row': '2', 'col': '4', 'order': '2', 'col_other': '2', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'speed', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; speed ; 2 }'}, 'pilot'], 'result': 'uli schwenk', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; speed ; 2 } ; pilot }'}, 'uli schwenk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; speed ; 2 } ; pilot } ; uli schwenk } = true', 'tointer': 'select the row whose speed record of all rows is 2nd maximum . the pilot record of this row is uli schwenk .'}

eq { hop { nth_argmax { all_rows ; speed ; 2 } ; pilot } ; uli schwenk } = true

select the row whose speed record of all rows is 2nd maximum . the pilot record of this row is uli schwenk .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'speed_5': 5, '2_6': 6, 'pilot_7': 7, 'uli schwenk_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'speed_5': 'speed', '2_6': '2', 'pilot_7': 'pilot', 'uli schwenk_8': 'uli schwenk'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'speed_5': [0], '2_6': [0], 'pilot_7': [1], 'uli schwenk_8': [2]}

['position', 'pilot', 'glider', 'speed', 'distance']

[['1', 'mario kiessling', 'ventus 2ax', '128.8 km / h', '240.5 km'], ['2', 'uli schwenk', 'ventus 2ax', '128.1 km / h', '240.5 km'], ['3', 'carlos rocca vidal', 'ventus 2b', '127.6 km / h', '240.5 km'], ['4', 'sebastian kawa', 'diana 2', '127.1 km / h', '240.5 km'], ['5', 'thomas gostner', 'diana 2', '126.3 km / h', '240.5 km'], ['6', 'graham parker', 'asg 29', '125.7 km / h', '240.5 km'], ['7', 'tilo holighaus', 'ventus 2ax', '125.3 km / h', '240.5 km'], ['8', 'wolfgang janowitsch', 'ventus 2cax', '124.2 km / h', '240.5 km'], ['9', 'heimo demmerer', 'ventus 2b', '124.1 km / h', '240.5 km'], ['10', 'eduard supersperger', 'ventus 2b', '124.0 km / h', '240.5 km'], ['10', 'stanislaw wujczak', 'asg 29', '123.9 km / h', '240.5 km'], ['10', 'petr krejcirik', 'ventus 2ax', '121.4 km / h', '240.5 km'], ['10', 'rene vidal', 'ventus 2c', '117.1 km / h', '240.5 km'], ['10', 'patrick puskeiler', 'discus 2ax', '111.1 km / h', '240.5 km'], ['10', 'olli teronen', 'asg 29', '95 km / h', '240.5 km']]

1940 vfl season

https://en.wikipedia.org/wiki/1940_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-9.html.csv

aggregation

in the 1940 vfl season , the average crowd size was 12,667 .

{'scope': 'all', 'col': '6', 'type': 'average', 'result': '12,667', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'crowd'], 'result': '12,667', 'ind': 0, 'tostr': 'avg { all_rows ; crowd }'}, '12,667'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; crowd } ; 12,667 } = true', 'tointer': 'the average of the crowd record of all rows is 12,667 .'}

round_eq { avg { all_rows ; crowd } ; 12,667 } = true

the average of the crowd record of all rows is 12,667 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'crowd_4': 4, '12,667_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'crowd_4': 'crowd', '12,667_5': '12,667'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'crowd_4': [0], '12,667_5': [1]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['geelong', '12.18 ( 90 )', 'hawthorn', '6.10 ( 46 )', 'corio oval', '4000', '22 june 1940'], ['fitzroy', '10.30 ( 90 )', 'south melbourne', '10.17 ( 77 )', 'brunswick street oval', '12000', '22 june 1940'], ['carlton', '16.20 ( 116 )', 'north melbourne', '18.12 ( 120 )', 'princes park', '13000', '22 june 1940'], ['st kilda', '16.16 ( 112 )', 'melbourne', '17.21 ( 123 )', 'junction oval', '13000', '22 june 1940'], ['richmond', '12.5 ( 77 )', 'essendon', '12.10 ( 82 )', 'punt road oval', '19000', '22 june 1940'], ['footscray', '15.10 ( 100 )', 'collingwood', '12.12 ( 84 )', 'western oval', '15000', '22 june 1940']]

fred funk

https://en.wikipedia.org/wiki/Fred_Funk

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1646050-6.html.csv

comparative

fred funk has played in more u.s. open events than pga championship events .

{'row_1': '2', 'row_2': '4', 'col': '6', 'col_other': '1', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'us open'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose tournament record fuzzily matches to us open .', 'tostr': 'filter_eq { all_rows ; tournament ; us open }'}, 'events'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; tournament ; us open } ; events }', 'tointer': 'select the rows whose tournament record fuzzily matches to us open . take the events record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'tournament', 'pga championship'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship .', 'tostr': 'filter_eq { all_rows ; tournament ; pga championship }'}, 'events'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; tournament ; pga championship } ; events }', 'tointer': 'select the rows whose tournament record fuzzily matches to pga championship . take the events record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; tournament ; us open } ; events } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; events } } = true', 'tointer': 'select the rows whose tournament record fuzzily matches to us open . take the events record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the events record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; tournament ; us open } ; events } ; hop { filter_eq { all_rows ; tournament ; pga championship } ; events } } = true

select the rows whose tournament record fuzzily matches to us open . take the events record of this row . select the rows whose tournament record fuzzily matches to pga championship . take the events record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'num_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'tournament_7': 7, 'us open_8': 8, 'events_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'tournament_11': 11, 'pga championship_12': 12, 'events_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'num_hop_2': 'num_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'tournament_7': 'tournament', 'us open_8': 'us open', 'events_9': 'events', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'tournament_11': 'tournament', 'pga championship_12': 'pga championship', 'events_13': 'events'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'tournament_7': [0], 'us open_8': [0], 'events_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'tournament_11': [1], 'pga championship_12': [1], 'events_13': [3]}

['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made']

[['masters tournament', '0', '0', '0', '1', '12', '4'], ['us open', '0', '0', '2', '4', '22', '13'], ['the open championship', '0', '0', '0', '0', '6', '2'], ['pga championship', '0', '1', '3', '5', '18', '15'], ['totals', '0', '1', '5', '10', '58', '34']]

lloyd ruby

https://en.wikipedia.org/wiki/Lloyd_Ruby

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1235044-1.html.csv

aggregation

the average rank that lloyd ruby had was a rank of 11.53 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '11.53', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'rank'], 'result': '11.53', 'ind': 0, 'tostr': 'avg { all_rows ; rank }'}, '11.53'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; rank } ; 11.53 } = true', 'tointer': 'the average of the rank record of all rows is 11.53 .'}

round_eq { avg { all_rows ; rank } ; 11.53 } = true

the average of the rank record of all rows is 11.53 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'rank_4': 4, '11.53_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'rank_4': 'rank', '11.53_5': '11.53'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'rank_4': [0], '11.53_5': [1]}

['year', 'start', 'qual', 'rank', 'finish', 'laps']

[['1960', '12', '144.208', '15', '7', '200'], ['1961', '25', '146.909', '2', '8', '200'], ['1962', '24', '146.520', '24', '8', '200'], ['1963', '19', '149.123', '15', '13', '200'], ['1964', '7', '153.932', '8', '3', '200'], ['1965', '9', '157.246', '9', '11', '184'], ['1966', '5', '162.433', '5', '11', '166'], ['1967', '7', '165.229', '8', '33', '3'], ['1968', '5', '167.613', '5', '5', '200'], ['1969', '20', '166.428', '20', '20', '105'], ['1970', '25', '168.895', '6', '27', '54'], ['1971', '7', '173.821', '7', '11', '174'], ['1972', '11', '181.415', '20', '6', '196'], ['1973', '15', '191.622', '18', '27', '21'], ['1974', '18', '181.699', '20', '9', '187'], ['1975', '6', '186.984', '7', '32', '7'], ['1976', '30', '186.480', '7', '11', '100'], ['1977', '19', '190.840', '11', '27', '34']]

2002 u.s. open ( golf )

https://en.wikipedia.org/wiki/2002_U.S._Open_%28golf%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16299790-7.html.csv

aggregation

the us open paid out $ 3,164,543 of money to the top 10 finishers .

{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '$ 3,164,543', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'money'], 'result': '$ 3,164,543', 'ind': 0, 'tostr': 'sum { all_rows ; money }'}, '$ 3,164,543'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; money } ; $ 3,164,543 } = true', 'tointer': 'the sum of the money record of all rows is $ 3,164,543 .'}

round_eq { sum { all_rows ; money } ; $ 3,164,543 } = true

the sum of the money record of all rows is $ 3,164,543 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'money_4': 4, '$3,164,543_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'money_4': 'money', '$3,164,543_5': '$ 3,164,543'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'money_4': [0], '$3,164,543_5': [1]}

['place', 'player', 'country', 'score', 'to par', 'money']

[['1', 'tiger woods', 'united states', '67 + 68 + 70 + 72 = 277', '- 3', '1000000'], ['2', 'phil mickelson', 'united states', '70 + 73 + 67 + 70 = 280', 'e', '585000'], ['3', 'jeff maggert', 'united states', '69 + 73 + 68 + 72 = 282', '+ 2', '362356'], ['4', 'sergio garcía', 'spain', '68 + 74 + 67 + 74 = 283', '+ 3', '252546'], ['t5', 'nick faldo', 'england', '70 + 76 + 66 + 73 = 285', '+ 5', '182882'], ['t5', 'scott hoch', 'united states', '71 + 75 + 70 + 69 = 285', '+ 5', '182882'], ['t5', 'billy mayfair', 'united states', '69 + 74 + 68 + 74 = 285', '+ 5', '182882'], ['t8', 'tom byrum', 'united states', '72 + 72 + 70 + 72 = 286', '+ 6', '138665'], ['t8', 'pádraig harrington', 'ireland', '70 + 68 + 73 + 75 = 286', '+ 6', '138665'], ['t8', 'nick price', 'zimbabwe', '72 + 75 + 69 + 70 = 286', '+ 6', '138665']]

north american catamaran racing association

https://en.wikipedia.org/wiki/North_American_Catamaran_Racing_Association

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17002889-1.html.csv

ordinal

considering the sailboats in the the north american catamaran racing association , the model 5.8 has the second highest sail area .

{'row': '17', 'col': '4', 'order': '2', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'sail area', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; sail area ; 2 }'}, 'model'], 'result': '5.8', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; sail area ; 2 } ; model }'}, '5.8'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; sail area ; 2 } ; model } ; 5.8 } = true', 'tointer': 'select the row whose sail area record of all rows is 2nd maximum . the model record of this row is 5.8 .'}

eq { hop { nth_argmax { all_rows ; sail area ; 2 } ; model } ; 5.8 } = true

select the row whose sail area record of all rows is 2nd maximum . the model record of this row is 5.8 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'sail area_5': 5, '2_6': 6, 'model_7': 7, '5.8_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmax_0': 'nth_argmax', 'all_rows_4': 'all_rows', 'sail area_5': 'sail area', '2_6': '2', 'model_7': 'model', '5.8_8': '5.8'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'sail area_5': [0], '2_6': [0], 'model_7': [1], '5.8_8': [2]}

['model', 'length over all', 'beam', 'sail area', 'crew', 'comments']

[['14sq', '4.5 m', '2.44', '14 m square', '1', 'daggerboards'], ['4.5', '4.50 m', '2.44 m', '17.5 m square', '1 - 2', 'skegs'], ['460', '4.50 m', '2.35 m', '15.2 m square', '1 - 2', 'skegs'], ['blast', '4.80 m', '2.45 m', '15.6 m square', '1 - 2', 'skegs design : alain comyn'], ['16sq', '5.0 m', '2.5 m', '16 m square', '1', 'daggerboards'], ['5.0', '5.0 m', '2.44 m', '19 m square', '2', 'skegs design : roy seaman'], ['500', '5.0 m', '2.44 m', '17.6 m square', '1 - 2', 'skegs'], ['5.2', '5.2 m', '2.44 m', '20.43 m square', '2', 'daggerboards'], ['f17', '5.20 m', '2.44 m', '15.25 m square', '1', 'daggerboards'], ['nacra 17', '5.25 m', '2.59 m', '18.25 m square', '2', 'curved daggerboards design : morelli und melvin'], ['18sq', '5.48 m', '3.35 m', '18 m square', '1', 'daggerboards'], ['f18 inter 18', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : morelli und melvin'], ['f18 inter 2', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : alain comyn'], ['f18 infusion', '5.52 m', '2.6 m', '20.45 / 21.15 m square', '2', 'f18 class boat design : morelli und melvin'], ['5.7', '5.67 m', '2.44 m', '21.3 m square', '2', 'skegs'], ['570', '5.65 m', '2.44 m', '21.1 m square', '2', 'skegs'], ['5.8', '5.8 m', '2.5 m', '22.8 m square', '2', 'daggerboards design : roy seaman'], ['580', '5.8 m', '2.44 m', '22.1 m square', '2', 'daggerboards'], ['6.0', '6.10 m', '2.59 m', '24.5 m square', '2', 'daggerboards'], ['n20', '6.12 m', '2.6 m', '20.45 / 24.9 m square', '2', 'formula 20 class boat']]

john garamendi

https://en.wikipedia.org/wiki/John_Garamendi

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1602620-1.html.csv

ordinal

the second time that john garamendi was elected to office was in 1976 .

{'row': '2', 'col': '4', 'order': '2', 'col_other': 'n/a', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}

{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'elected', '2'], 'result': '1976', 'ind': 0, 'tostr': 'nth_min { all_rows ; elected ; 2 }', 'tointer': 'the 2nd minimum elected record of all rows is 1976 .'}, '1976'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; elected ; 2 } ; 1976 } = true', 'tointer': 'the 2nd minimum elected record of all rows is 1976 .'}

eq { nth_min { all_rows ; elected ; 2 } ; 1976 } = true

the 2nd minimum elected record of all rows is 1976 .

2

2

{'eq_1': 1, 'result_2': 2, 'nth_min_0': 0, 'all_rows_3': 3, 'elected_4': 4, '2_5': 5, '1976_6': 6}

{'eq_1': 'eq', 'result_2': 'true', 'nth_min_0': 'nth_min', 'all_rows_3': 'all_rows', 'elected_4': 'elected', '2_5': '2', '1976_6': '1976'}

{'eq_1': [2], 'result_2': [], 'nth_min_0': [1], 'all_rows_3': [0], 'elected_4': [0], '2_5': [0], '1976_6': [1]}

['office', 'type', 'location', 'elected', 'term began', 'term ended']

[['state assemblyman', 'legislature', 'sacramento', '1974', 'december 7 , 1974', 'december 2 , 1976'], ['state senator', 'legislature', 'sacramento', '1976', 'december 2 , 1976', 'december 8 , 1980'], ['state senator', 'legislature', 'sacramento', '1980', 'december 8 , 1980', 'december 3 , 1984'], ['state senator', 'legislature', 'sacramento', '1984', 'december 3 , 1984', 'december 5 , 1988'], ['state senator', 'legislature', 'sacramento', '1988', 'december 5 , 1988', 'december 3 , 1990'], ['insurance commissioner', 'executive', 'sacramento', '1990', 'january 7 , 1991', 'january 2 , 1995'], ['insurance commissioner', 'executive', 'sacramento', '2002', 'january 6 , 2003', 'january 8 , 2007'], ['lieutenant governor', 'executive', 'sacramento', '2006', 'january 8 , 2007', 'november 5 , 2009'], ['us representative', 'legislative', 'washington , dc', '2009', 'november 5 , 2009', 'january 3 , 2011']]

portugal in the eurovision song contest 1996

https://en.wikipedia.org/wiki/Portugal_in_the_Eurovision_Song_Contest_1996

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18994360-1.html.csv

count

in the 1996 eurovision song contest , two singers from portugal scored over 90 points .

{'scope': 'all', 'criterion': 'greater_than', 'value': '90', 'result': '2', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater', 'args': ['all_rows', 'points', '90'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is greater than 90 .', 'tostr': 'filter_greater { all_rows ; points ; 90 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_greater { all_rows ; points ; 90 } }', 'tointer': 'select the rows whose points record is greater than 90 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater { all_rows ; points ; 90 } } ; 2 } = true', 'tointer': 'select the rows whose points record is greater than 90 . the number of such rows is 2 .'}

eq { count { filter_greater { all_rows ; points ; 90 } } ; 2 } = true

select the rows whose points record is greater than 90 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_0': 0, 'all_rows_4': 4, 'points_5': 5, '90_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_0': 'filter_greater', 'all_rows_4': 'all_rows', 'points_5': 'points', '90_6': '90', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_0': [1], 'all_rows_4': [0], 'points_5': [0], '90_6': [0], '2_7': [2]}

['draw', 'singer', 'song', 'points', 'place']

[['1', 'vnia maroti', 'start stop', '33', '10'], ['2', 'tó leal', 'eu mesmo', '42', '8'], ['3', 'patricia antunes', 'canto em português', '91', '2'], ['4', 'barbara reis', 'a minha ilha', '43', '7'], ['5', 'elaisa', 'ai a noite', '49', '6'], ['6', 'somseis', 'a canção da paz', '76', '3'], ['7', 'cristina castro pereira', 'ganhamos o ceu', '63', '4'], ['8', 'lúcia moniz', 'o meu coração não tem cor', '95', '1'], ['9', 'pedro miguéis', 'prazer em conhecer', '54', '5'], ['10', 'joão portugal', 'top model', '34', '9']]

1953 world wrestling championships

https://en.wikipedia.org/wiki/1953_World_Wrestling_Championships

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16869142-1.html.csv

count

9 nations were represented in the 1953 world wrestling championships .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '9', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'nation'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose nation record is arbitrary .', 'tostr': 'filter_all { all_rows ; nation }'}], 'result': '9', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; nation } }', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 9 .'}, '9'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; nation } } ; 9 } = true', 'tointer': 'select the rows whose nation record is arbitrary . the number of such rows is 9 .'}

eq { count { filter_all { all_rows ; nation } } ; 9 } = true

select the rows whose nation record is arbitrary . the number of such rows is 9 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'nation_5': 5, '9_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'nation_5': 'nation', '9_6': '9'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'nation_5': [0], '9_6': [2]}

['rank', 'nation', 'gold', 'silver', 'bronze', 'total']

[['1', 'soviet union', '5', '1', '1', '7'], ['2', 'sweden', '3', '1', '0', '4'], ['3', 'finland', '0', '2', '1', '3'], ['4', 'hungary', '0', '2', '0', '2'], ['5', 'italy', '0', '1', '3', '4'], ['6', 'turkey', '0', '1', '0', '1'], ['7', 'belgium', '0', '0', '1', '1'], ['7', 'lebanon', '0', '0', '1', '1'], ['7', 'switzerland', '0', '0', '1', '1'], ['total', 'total', '8', '8', '8', '24']]

1937 vfl season

https://en.wikipedia.org/wiki/1937_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10806194-8.html.csv

superlative

in the 1937 vfl season , the highest attendance among games that took place on 12 june 1937 occurred at punt road oval .

{'scope': 'subset', 'col_superlative': '6', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '5', 'subset': {'col': '7', 'criterion': 'equal', 'value': '12 june 1937'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '12 june 1937'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 12 june 1937 }', 'tointer': 'select the rows whose date record fuzzily matches to 12 june 1937 .'}, 'crowd'], 'result': None, 'ind': 1, 'tostr': 'argmax { filter_eq { all_rows ; date ; 12 june 1937 } ; crowd }'}, 'venue'], 'result': 'punt road oval', 'ind': 2, 'tostr': 'hop { argmax { filter_eq { all_rows ; date ; 12 june 1937 } ; crowd } ; venue }'}, 'punt road oval'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmax { filter_eq { all_rows ; date ; 12 june 1937 } ; crowd } ; venue } ; punt road oval } = true', 'tointer': 'select the rows whose date record fuzzily matches to 12 june 1937 . select the row whose crowd record of these rows is maximum . the venue record of this row is punt road oval .'}

eq { hop { argmax { filter_eq { all_rows ; date ; 12 june 1937 } ; crowd } ; venue } ; punt road oval } = true

select the rows whose date record fuzzily matches to 12 june 1937 . select the row whose crowd record of these rows is maximum . the venue record of this row is punt road oval .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmax_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'date_6': 6, '12 june 1937_7': 7, 'crowd_8': 8, 'venue_9': 9, 'punt road oval_10': 10}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmax_1': 'argmax', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'date_6': 'date', '12 june 1937_7': '12 june 1937', 'crowd_8': 'crowd', 'venue_9': 'venue', 'punt road oval_10': 'punt road oval'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmax_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'date_6': [0], '12 june 1937_7': [0], 'crowd_8': [1], 'venue_9': [2], 'punt road oval_10': [3]}

['home team', 'home team score', 'away team', 'away team score', 'venue', 'crowd', 'date']

[['geelong', '16.13 ( 109 )', 'st kilda', '11.15 ( 81 )', 'corio oval', '12600', '12 june 1937'], ['essendon', '13.11 ( 89 )', 'collingwood', '19.14 ( 128 )', 'windy hill', '13000', '12 june 1937'], ['richmond', '14.24 ( 108 )', 'carlton', '13.19 ( 97 )', 'punt road oval', '27000', '12 june 1937'], ['hawthorn', '12.10 ( 82 )', 'melbourne', '15.15 ( 105 )', 'glenferrie oval', '18000', '14 june 1937'], ['fitzroy', '14.15 ( 99 )', 'footscray', '8.14 ( 62 )', 'brunswick street oval', '20000', '14 june 1937'], ['south melbourne', '16.18 ( 114 )', 'north melbourne', '10.10 ( 70 )', 'lake oval', '16000', '14 june 1937']]

le tour de filipinas

https://en.wikipedia.org/wiki/Le_Tour_de_Filipinas

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10694950-4.html.csv

superlative

the 2004 air21 tour pilipinas was the tour that had the highest amount of stages .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '3', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '2', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'stages'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; stages }'}, 'name'], 'result': 'air21 tour pilipinas', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; stages } ; name }'}, 'air21 tour pilipinas'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; stages } ; name } ; air21 tour pilipinas } = true', 'tointer': 'select the row whose stages record of all rows is maximum . the name record of this row is air21 tour pilipinas .'}

eq { hop { argmax { all_rows ; stages } ; name } ; air21 tour pilipinas } = true

select the row whose stages record of all rows is maximum . the name record of this row is air21 tour pilipinas .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'stages_5': 5, 'name_6': 6, 'air21 tour pilipinas_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'stages_5': 'stages', 'name_6': 'name', 'air21 tour pilipinas_7': 'air21 tour pilipinas'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'stages_5': [0], 'name_6': [1], 'air21 tour pilipinas_7': [2]}

['year', 'name', 'date', 'stages', 'distance', 'winner', 'time']

[['2002', 'fedex tour of calabarzon', '30 may - 2 june', '4', '517.7 km', 'santi barnachea ( phi )', '12:41:13'], ['2003', 'air21 tour pilipinas', '16 april - 11 may', '15', '2849.8 km', 'arnel quirimit ( phi )', '55:29:20'], ['2004', 'air21 tour pilipinas', '15 april - 2 may', '17', '2849.8 km', 'rhyan tanguilig ( phi )', '70:28:59'], ['2005', 'golden tour 50 05', '26 may - 5 june', '10', '1492 km', 'warren davadilla ( phi )', '37:20:55'], ['2006', 'padyak pinoy tour pilipinas', '12 - 18 may', '8', '1219.4 km', 'santi barnachea ( phi )', '31:10:03'], ['2007', 'padyak pinoy', '17 - 29 may', '10', '1500 km', 'victor espiritu ( phi )', '33:02:38'], ['2008', 'cancelled', 'cancelled', 'cancelled', 'cancelled', 'cancelled', 'cancelled'], ['2009', 'padyak pinoy tour of champions', '8 - 15 may', '8', '1070 km', 'joel calderon ( phi )', '29:52:33'], ['2010', 'le tour de filipinas', '12 - 20 april', '4', '468.8 km', 'david mccann ( irl )', '11:29:20'], ['2011', 'le tour de filipinas', '16 - 19 april', '4', '468.8 km', 'rahim emami ( iri )', '12:15:34'], ['2012', 'le tour de filipinas', '14 - 17 april', '4', '502 km', 'baler ravina ( phi )', '13:20:32'], ['2013', 'le tour de filipinas', '13 - 16 april', '4', '616 km', 'ghader mizbani ( iri )', '16:38:37']]

wfcr

https://en.wikipedia.org/wiki/WFCR

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1540742-1.html.csv

majority

all wfcr are listed in the state of massachusetts .

{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'massachusetts', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'city of license', 'massachusetts'], 'result': True, 'ind': 0, 'tointer': 'for the city of license records of all rows , all of them fuzzily match to massachusetts .', 'tostr': 'all_eq { all_rows ; city of license ; massachusetts } = true'}

all_eq { all_rows ; city of license ; massachusetts } = true

for the city of license records of all rows , all of them fuzzily match to massachusetts .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'city of license_3': 3, 'massachusetts_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'city of license_3': 'city of license', 'massachusetts_4': 'massachusetts'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'city of license_3': [0], 'massachusetts_4': [0]}

['call sign', 'frequency mhz', 'city of license', 'erp w', 'class', 'fcc info']

[['w291ch', '106.1', 'pittsfield , massachusetts', '10', 'd', 'fcc'], ['w242at', '96.3', 'williamstown , massachusetts', '250', 'd', 'fcc'], ['w252bg', '98.3', 'lee , massachusetts', '13', 'd', 'fcc'], ['w254au', '98.7', 'great barrington , massachusetts', '250', 'd', 'fcc'], ['w266aw', '101.1', 'north adams , massachusetts', '10', 'd', 'fcc']]

henlopen conference

https://en.wikipedia.org/wiki/Henlopen_Conference

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13054553-8.html.csv

comparative

the indians had more wins in the division record than the blue raiders .

{'row_1': '2', 'row_2': '3', 'col': '3', 'col_other': '2', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'greater', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'indians'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose team record fuzzily matches to indians .', 'tostr': 'filter_eq { all_rows ; team ; indians }'}, 'division record'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; team ; indians } ; division record }', 'tointer': 'select the rows whose team record fuzzily matches to indians . take the division record record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'team', 'blue raiders'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose team record fuzzily matches to blue raiders .', 'tostr': 'filter_eq { all_rows ; team ; blue raiders }'}, 'division record'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; team ; blue raiders } ; division record }', 'tointer': 'select the rows whose team record fuzzily matches to blue raiders . take the division record record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; team ; indians } ; division record } ; hop { filter_eq { all_rows ; team ; blue raiders } ; division record } } = true', 'tointer': 'select the rows whose team record fuzzily matches to indians . take the division record record of this row . select the rows whose team record fuzzily matches to blue raiders . take the division record record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; team ; indians } ; division record } ; hop { filter_eq { all_rows ; team ; blue raiders } ; division record } } = true

select the rows whose team record fuzzily matches to indians . take the division record record of this row . select the rows whose team record fuzzily matches to blue raiders . take the division record record of this row . the first record is greater than the second record .

5

5

{'greater_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'team_7': 7, 'indians_8': 8, 'division record_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'blue raiders_12': 12, 'division record_13': 13}

{'greater_4': 'greater', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'team_7': 'team', 'indians_8': 'indians', 'division record_9': 'division record', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'blue raiders_12': 'blue raiders', 'division record_13': 'division record'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'indians_8': [0], 'division record_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'blue raiders_12': [1], 'division record_13': [3]}

['school', 'team', 'division record', 'overall record', 'season outcome']

[['delmar', 'wildcats', '6 - 0', '11 - 1', 'loss in div ii championship game'], ['indian river', 'indians', '5 - 1', '8 - 3', 'loss in first round of div ii playoffs'], ['woodbridge', 'blue raiders', '4 - 2', '6 - 4', 'failed to make playoffs'], ['laurel', 'bulldogs', '3 - 3', '6 - 4', 'failed to make playoffs'], ['smyrna', 'eagles', '2 - 4', '3 - 7', 'failed to make playoffs'], ['seaford', 'blue jays', '1 - 5', '2 - 8', 'failed to make playoffs'], ['lake forest', 'spartans', '1 - 5', '1 - 9', 'failed to make playoffs']]

the mole ( tv series )

https://en.wikipedia.org/wiki/The_Mole_%28TV_series%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-178242-2.html.csv

aggregation

the average total prize money per season of the mole is 135000 .

{'scope': 'all', 'col': '6', 'type': 'average', 'result': '135000', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'total prize money'], 'result': '135000', 'ind': 0, 'tostr': 'avg { all_rows ; total prize money }'}, '135000'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; total prize money } ; 135000 } = true', 'tointer': 'the average of the total prize money record of all rows is 135000 .'}

round_eq { avg { all_rows ; total prize money } ; 135000 } = true

the average of the total prize money record of all rows is 135000 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'total prize money_4': 4, '135000_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'total prize money_4': 'total prize money', '135000_5': '135000'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'total prize money_4': [0], '135000_5': [1]}

['season', 'year', 'mole', 'winner', 'runner - up', 'total prize money', 'potential prize money', 'destination']

[['1', '2000', 'alan mason', 'jan moody', 'abby coleman', '115000', '200000', 'australia ( tasmania )'], ['2', '2001', 'michael laffy', 'brooke marshall', 'hal pritchard', '100000', '255000', 'australia ( victoria )'], ['3', '2002', 'alaina taylor', 'crystal - rose cluff', 'marc jongebloed', '108000', '416000', 'australia ( gold coast )'], ['4', '2003', 'petrina edge', 'shaun faulkner', 'nathan beves', '104000', '531000', 'new caledonia'], ['5', '2005', 'john whitehall', 'liz cantor', 'craig murell', '203000', '539000', 'new zealand'], ['6', '2013', 'erin dooley', 'hillal kara - ali', 'aisha jefcoate', '180000', '250000', 'australia']]

india national under - 23 football team results

https://en.wikipedia.org/wiki/India_national_under-23_football_team_results

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25428629-1.html.csv

unique

the only time when india scored into its own goal in the india national under-23 football team was at the game on jun. 23 , 2011 .

{'scope': 'all', 'row': '4', 'col': '7', 'col_other': '1', 'criterion': 'equal', 'value': 'own goal', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'indian scorers', 'own goal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose indian scorers record fuzzily matches to own goal .', 'tostr': 'filter_eq { all_rows ; indian scorers ; own goal }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; indian scorers ; own goal } }', 'tointer': 'select the rows whose indian scorers record fuzzily matches to own goal . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'indian scorers', 'own goal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose indian scorers record fuzzily matches to own goal .', 'tostr': 'filter_eq { all_rows ; indian scorers ; own goal }'}, 'date'], 'result': '23 june 2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; indian scorers ; own goal } ; date }'}, '23 june 2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; indian scorers ; own goal } ; date } ; 23 june 2011 }', 'tointer': 'the date record of this unqiue row is 23 june 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; indian scorers ; own goal } } ; eq { hop { filter_eq { all_rows ; indian scorers ; own goal } ; date } ; 23 june 2011 } } = true', 'tointer': 'select the rows whose indian scorers record fuzzily matches to own goal . there is only one such row in the table . the date record of this unqiue row is 23 june 2011 .'}

and { only { filter_eq { all_rows ; indian scorers ; own goal } } ; eq { hop { filter_eq { all_rows ; indian scorers ; own goal } ; date } ; 23 june 2011 } } = true

select the rows whose indian scorers record fuzzily matches to own goal . there is only one such row in the table . the date record of this unqiue row is 23 june 2011 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'indian scorers_7': 7, 'own goal_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '23 june 2011_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'indian scorers_7': 'indian scorers', 'own goal_8': 'own goal', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '23 june 2011_10': '23 june 2011'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'indian scorers_7': [0], 'own goal_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '23 june 2011_10': [3]}

['date', 'tournament', 'location', 'opponent', 'stadium', 'score', 'indian scorers']

[['23 february 2011', '2012 olympic qualifier', 'pune , india', 'myanmar', 'balewadi sports complex', '2 - 1', 'jeje lalpekhlua , malsawmfela'], ['9 march 2011', '2012 olympic qualifier', 'yangon , myanmar', 'myanmar', 'thuwunna stadium', '1 - 1', 'chinadorai sabeeth'], ['19 june 2011', '2012 olympic qualifier', 'doha , qatar', 'qatar', 'jassim bin hamad stadium', '1 - 3', 'jeje lalpekhlua'], ['23 june 2011', '2012 olympic qualifier', 'pune , india', 'qatar', 'balewadi sports complex', '1 - 1', 'own goal'], ['25 june 2012', '2014 afc u - 22 asian cup qualifiers', 'muscat , oman', 'iraq', 'royal oman police stadium', '1 - 2', 'alwyn george'], ['28 june 2012', '2014 afc u - 22 asian cup qualifiers', 'muscat , oman', 'united arab emirates', 'royal oman police stadium', '1 - 1', 'romeo fernandes']]

suwon samsung bluewings

https://en.wikipedia.org/wiki/Suwon_Samsung_Bluewings

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1054817-4.html.csv

majority

adidas has been the kit supplier for the samsung bluewings for most of the last twenty five years .

{'scope': 'all', 'col': '2', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'adidas', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'kit supplier', 'adidas'], 'result': True, 'ind': 0, 'tointer': 'for the kit supplier records of all rows , most of them fuzzily match to adidas .', 'tostr': 'most_eq { all_rows ; kit supplier ; adidas } = true'}

most_eq { all_rows ; kit supplier ; adidas } = true

for the kit supplier records of all rows , most of them fuzzily match to adidas .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'kit supplier_3': 3, 'adidas_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'kit supplier_3': 'kit supplier', 'adidas_4': 'adidas'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'kit supplier_3': [0], 'adidas_4': [0]}

['year', 'kit supplier', 'sponsor', 'shirt printing', 'notes']

[['1996', 'rapido', 'samsung electronics', 'bluewings', 'team name'], ['1997', 'rapido', 'samsung electronics', '名品 + 1', 'television brand'], ['1998', 'rapido', 'samsung electronics', '名品 + 1', 'television brand'], ['1999', 'rapido', 'samsung electronics', 'anycall', 'mobile phone brand'], ['2000', 'rapido', 'samsung electronics', 'anycall', 'mobile phone brand'], ['2001', 'rapido', 'samsung electronics', 'sensq bluewin', 'laptop brand air conditioner brand'], ['2002', 'adidas', 'samsung electronics', 'hauzen', 'electronics brand'], ['2003', 'adidas', 'samsung electronics', 'hauzen', 'electronics brand'], ['2004', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2005', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2006', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2007', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2008', 'adidas', 'samsung electronics', 'pavv', 'television brand'], ['2009', 'adidas', 'samsung electronics', 'samsung pavv', 'television brand'], ['2010', 'adidas', 'samsung electronics', 'samsung pavv', 'television brand'], ['2011', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand'], ['2012', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand'], ['2013', 'adidas', 'samsung electronics', 'samsung smart tv', 'television brand']]

1970 cfl draft

https://en.wikipedia.org/wiki/1970_CFL_Draft

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26996293-2.html.csv

unique

in the second round of the 1970 cfl draft , there was only one fl or flankerback drafted .

{'scope': 'all', 'row': '1', 'col': '4', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'fl', 'subset': None}

{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'position', 'fl'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose position record fuzzily matches to fl .', 'tostr': 'filter_eq { all_rows ; position ; fl }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; position ; fl } } = true', 'tointer': 'select the rows whose position record fuzzily matches to fl . there is only one such row in the table .'}

only { filter_eq { all_rows ; position ; fl } } = true

select the rows whose position record fuzzily matches to fl . there is only one such row in the table .

2

2

{'only_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'position_4': 4, 'fl_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'position_4': 'position', 'fl_5': 'fl'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'position_4': [0], 'fl_5': [0]}

['pick', 'cfl team', 'player', 'position', 'college']

[['10', 'winnipeg ( 2 )', 'john senst', 'fl', 'simon fraser'], ['11', 'montreal ( 1 )', 'burns mcpherson', 'hb', 'st francis xavier'], ['12', 'edmonton ( 2 )', 'jim henshall', 'hb', 'western'], ['13', 'bc lions ( 2 )', "tony d'aloisio", 'fb', 'windsor'], ['14', 'winnipeg ( 3 ) via hamilton', 'rick sugden', 'hb', 'simon fraser'], ['15', 'calgary ( 3 )', 'don lumb', 'ot', 'british columbia'], ['16', 'toronto ( 1 )', 'paul brown', 'ot', 'waterloo lutheran'], ['17', 'saskatchewan ( 2 )', 'andre rancourt', 'de', 'ottawa']]

1967 new york giants season

https://en.wikipedia.org/wiki/1967_New_York_Giants_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16661087-1.html.csv

majority

most of the new york giants games in the 1967 football season had an attendance of over 40,000 .

{'scope': 'all', 'col': '5', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '40000', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'attendance', '40000'], 'result': True, 'ind': 0, 'tointer': 'for the attendance records of all rows , most of them are greater than 40000 .', 'tostr': 'most_greater { all_rows ; attendance ; 40000 } = true'}

most_greater { all_rows ; attendance ; 40000 } = true

for the attendance records of all rows , most of them are greater than 40000 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'attendance_3': 3, '40000_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'attendance_3': 'attendance', '40000_4': '40000'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'attendance_3': [0], '40000_4': [0]}

['week', 'date', 'opponent', 'result', 'attendance']

[['1', 'september 17 , 1967', 'st louis cardinals', 'w 37 - 20', '40801'], ['2', 'september 24 , 1967', 'dallas cowboys', 'l 38 - 24', '66209'], ['3', 'october 1 , 1967', 'washington redskins', 'l 38 - 34', '50266'], ['4', 'october 8 , 1967', 'new orleans saints', 'w 27 - 21', '62670'], ['5', 'october 15 , 1967', 'pittsburgh steelers', 'w 27 - 24', '39782'], ['6', 'october 22 , 1967', 'green bay packers', 'l 48 - 21', '62585'], ['7', 'october 29 , 1967', 'cleveland browns', 'w 38 - 34', '62903'], ['8', 'november 5 , 1967', 'minnesota vikings', 'l 27 - 24', '44960'], ['9', 'november 12 , 1967', 'chicago bears', 'l 34 - 7', '46223'], ['10', 'november 19 , 1967', 'pittsburgh steelers', 'w 28 - 20', '62982'], ['11', 'november 26 , 1967', 'philadelphia eagles', 'w 44 - 7', '63027'], ['12', 'december 3 , 1967', 'cleveland browns', 'l 24 - 14', '78594'], ['13', 'december 10 , 1967', 'detroit lions', 'l 30 - 7', '63011'], ['14', 'december 17 , 1967', 'st louis cardinals', 'w 37 - 14', '62955']]

new york state election , 1916

https://en.wikipedia.org/wiki/New_York_state_election%2C_1916

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15563550-6.html.csv

count

two of the people on the republican ticket have the first name frank .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'frank', 'result': '2', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'republican ticket', 'frank'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose republican ticket record fuzzily matches to frank .', 'tostr': 'filter_eq { all_rows ; republican ticket ; frank }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; republican ticket ; frank } }', 'tointer': 'select the rows whose republican ticket record fuzzily matches to frank . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; republican ticket ; frank } } ; 2 } = true', 'tointer': 'select the rows whose republican ticket record fuzzily matches to frank . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; republican ticket ; frank } } ; 2 } = true

select the rows whose republican ticket record fuzzily matches to frank . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'republican ticket_5': 5, 'frank_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'republican ticket_5': 'republican ticket', 'frank_6': 'frank', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'republican ticket_5': [0], 'frank_6': [0], '2_7': [2]}

['office', 'republican ticket', 'democratic ticket', 'socialist ticket', 'prohibition ticket', 'progressive ticket', 'independence league ticket']

[['governor', 'charles s whitman', 'samuel seabury', 'algernon lee', 'charles e welch', 'charles s whitman', 'charles s whitman'], ['lieutenant governor', 'edward schoeneck', 'thomas j kreuzer', 'stephen j mahoney', 'clarence z spriggs', 'l bradley dorr', 'edward schoeneck'], ['secretary of state', 'francis m hugo', 'frank m stage', 'pauline m newman', 'neil d cranmer', 'francis m hugo', 'francis m hugo'], ['comptroller', 'eugene m travis', 'joseph w masters', 'charles w noonan', 'george a norton', 'eugene m travis', 'joseph w masters'], ['attorney general', 'egburt e woodbury', 'william w farley', 's john block', 'claude w stowell', 'robert h elder', 'william a deford'], ['treasurer', 'james l wells', 'maurice s cohen', 'eugene wood', 'william j richardson', 'frank p tucker', 'james l wells'], ['state engineer', 'frank m williams', 'henry r beebe', 'george h warner', 'william b timbrell', 'frank m williams', 'frank m williams'], ['chief judge', 'frank h hiscock', 'almet f jenks', 'louis b boudin', 'erwin j baldwin', 'frank h hiscock', 'almet f jenks'], ['judge of the court of appeals', 'cuthbert w pound', 'john t norton', 'hezekiah d wilcox', 'coleridge a hart', 'cuthbert w pound', 'john t norton'], ['us senator', 'william m calder', 'william f mccombs', 'joseph d cannon', 'd leigh colvin', 'bainbridge colby', 'bainbridge colby']]

list of corporations by market capitalization

https://en.wikipedia.org/wiki/List_of_corporations_by_market_capitalization

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14094649-14.html.csv

count

among the corporations with the greatest market capitalization , 4 are in the oil and gas industry .

{'scope': 'all', 'criterion': 'equal', 'value': 'oil and gas', 'result': '4', 'col': '4', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'industry', 'oil and gas'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose industry record fuzzily matches to oil and gas .', 'tostr': 'filter_eq { all_rows ; industry ; oil and gas }'}], 'result': '4', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; industry ; oil and gas } }', 'tointer': 'select the rows whose industry record fuzzily matches to oil and gas . the number of such rows is 4 .'}, '4'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; industry ; oil and gas } } ; 4 } = true', 'tointer': 'select the rows whose industry record fuzzily matches to oil and gas . the number of such rows is 4 .'}

eq { count { filter_eq { all_rows ; industry ; oil and gas } } ; 4 } = true

select the rows whose industry record fuzzily matches to oil and gas . the number of such rows is 4 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'industry_5': 5, 'oil and gas_6': 6, '4_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'industry_5': 'industry', 'oil and gas_6': 'oil and gas', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'industry_5': [0], 'oil and gas_6': [0], '4_7': [2]}

['rank', 'name', 'headquarters', 'industry', 'market value ( usd million )']

[['1', 'exxon mobil', 'united states', 'oil and gas', '371631'], ['2', 'general electric', 'united states', 'conglomerate', '362527'], ['3', 'microsoft', 'united states', 'software industry', '281171'], ['4', 'citigroup', 'united states', 'banking', '238935'], ['5', 'bp', 'united kingdom', 'oil and gas', '233260'], ['6', 'bank of america', 'united states', 'banking', '211706'], ['7', 'royal dutch shell', 'the netherlands', 'oil and gas', '211280'], ['8', 'wal - mart', 'united states', 'retail', '196860'], ['9', 'toyota motor corporation', 'japan', 'automotive', '196731'], ['10', 'gazprom', 'russia', 'oil and gas', '196339']]

list of supernanny episodes

https://en.wikipedia.org/wiki/List_of_Supernanny_episodes

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-19897294-16.html.csv

ordinal

the peterfreund family was the second family to be aired in the 2010-11 supernanny season .

{'row': '2', 'col': '5', 'order': '2', 'col_other': '3', 'max_or_min': 'min_to_max', 'value_mentioned': 'no', 'scope': 'all', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'original air date', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; original air date ; 2 }'}, 'family / families'], 'result': 'the peterfreund family', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; original air date ; 2 } ; family / families }'}, 'the peterfreund family'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; original air date ; 2 } ; family / families } ; the peterfreund family } = true', 'tointer': 'select the row whose original air date record of all rows is 2nd minimum . the family / families record of this row is the peterfreund family .'}

eq { hop { nth_argmin { all_rows ; original air date ; 2 } ; family / families } ; the peterfreund family } = true

select the row whose original air date record of all rows is 2nd minimum . the family / families record of this row is the peterfreund family .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'original air date_5': 5, '2_6': 6, 'family / families_7': 7, 'the peterfreund family_8': 8}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'nth_argmin_0': 'nth_argmin', 'all_rows_4': 'all_rows', 'original air date_5': 'original air date', '2_6': '2', 'family / families_7': 'family / families', 'the peterfreund family_8': 'the peterfreund family'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'original air date_5': [0], '2_6': [0], 'family / families_7': [1], 'the peterfreund family_8': [2]}

['no in series', 'no in season', 'family / families', 'location ( s )', 'original air date']

[['us94', '1', 'the atkinson family', 'glen ellyn , il', '5 november 2010'], ['us95', '2', 'the peterfreund family', 'chandler , az', '12 november 2010'], ['us96', '3', 'the swift family', 'sacramento , ca', '19 november 2010'], ['us97', '4', 'the youngs family', 'whidbey island , washington', '3 december 2010'], ['us98', '5', 'the van acker family', 'oak view , ca', '10 december 2010'], ['us99', '6', 'the fernandez family', 'kissimmee , fl', '17 december 2010'], ['us100', '7', 'the george family', 'san antonio , tx', '7 january 2011'], ['us101', '8', 'the miller family', 'phoenix , az', '14 january 2011'], ['us102', '9', 'the colombo family', 'melbourne , fl', '21 january 2011'], ['us103', '10', 'the potter family', 'rochester , ny', '4 february 2011'], ['us104', '11', 'the merrill family', 'camp pendleton , ca', '18 february 2011'], ['us105', '12', 'the demott family', 'bayville , nj', '25 february 2011'], ['us106', '13', 'the froebrich family', 'fort mill , sc', '4 march 2011'], ['us107', '14', 'the federico family', 'las vegas , nv', '11 march 2011']]

2008 issf world cup final ( shotgun )

https://en.wikipedia.org/wiki/2008_ISSF_World_Cup_Final_%28shotgun%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18351792-6.html.csv

majority

most of the shooters in the 2008 issf world cup final were from countries other than the usa .

{'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'not_equal', 'value': 'usa', 'subset': None}

{'func': 'most_str_not_eq', 'args': ['all_rows', 'shooter', 'usa'], 'result': True, 'ind': 0, 'tointer': 'for the shooter records of all rows , most of them do not match to usa .', 'tostr': 'most_not_eq { all_rows ; shooter ; usa } = true'}

most_not_eq { all_rows ; shooter ; usa } = true

for the shooter records of all rows , most of them do not match to usa .

1

1

{'most_str_not_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'shooter_3': 3, 'usa_4': 4}

{'most_str_not_eq_0': 'most_str_not_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'shooter_3': 'shooter', 'usa_4': 'usa'}

{'most_str_not_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'shooter_3': [0], 'usa_4': [0]}

['shooter', 'event', 'rank points', 'score points', 'total']

[['georgios achilleos ( cyp )', 'wcf 2007', 'defending champion', 'defending champion', 'defending champion'], ['vincent hancock ( usa )', 'og beijing', 'olympic gold medalist', 'olympic gold medalist', 'olympic gold medalist'], ['tore brovold ( nor )', 'og beijing', 'olympic silver medalist', 'olympic silver medalist', 'olympic silver medalist'], ['anthony terras ( fra )', 'og beijing', 'olympic bronze medalist', 'olympic bronze medalist', 'olympic bronze medalist'], ['ariel mauricio flores ( mex )', 'wc kerrville', '15', '12', '27'], ['qu ridong ( chn )', 'wc beijing', '15', '10', '25'], ['andrea benelli ( ita )', 'wc belgrade', '10', '13', '23'], ['konstantin tsuranov ( rus )', 'wc beijing', '10', '10', '20'], ['jan sychra ( cze )', 'wc belgrade', '5', '13', '18'], ['valerio luchini ( ita )', 'wc kerrville', '8', '10', '18'], ['leos hlavacek ( cze )', 'wc suhl', '5', '11', '16'], ['abdullah alrashidi ( kuw )', 'wc belgrade', '3', '12', '15']]

eagles - giants rivalry

https://en.wikipedia.org/wiki/Eagles%E2%80%93Giants_rivalry

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16900662-10.html.csv

majority

the new york giants won most of their matches against the eagles between 2010 and 2013 .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'new york giants', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'winner', 'new york giants'], 'result': True, 'ind': 0, 'tointer': 'for the winner records of all rows , most of them fuzzily match to new york giants .', 'tostr': 'most_eq { all_rows ; winner ; new york giants } = true'}

most_eq { all_rows ; winner ; new york giants } = true

for the winner records of all rows , most of them fuzzily match to new york giants .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'winner_3': 3, 'new york giants_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'winner_3': 'winner', 'new york giants_4': 'new york giants'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'winner_3': [0], 'new york giants_4': [0]}

['year', 'date', 'winner', 'result', 'loser', 'location']

[['2010', 'november 21', 'philadelphia eagles', '27 - 17', 'new york giants', 'lincoln financial field'], ['2010', 'december 19', 'philadelphia eagles', '38 - 31', 'new york giants', 'new meadowlands stadium'], ['2011', 'september 25', 'new york giants', '29 - 16', 'philadelphia eagles', 'lincoln financial field'], ['2011', 'november 20', 'philadelphia eagles', '17 - 10', 'new york giants', 'metlife stadium'], ['2012', 'september 30', 'philadelphia eagles', '19 - 17', 'new york giants', 'lincoln financial field'], ['2012', 'december 30', 'new york giants', '42 - 7', 'philadelphia eagles', 'metlife stadium'], ['2013', 'october 6', 'philadelphia eagles', '36 - 21', 'new york giants', 'metlife stadium'], ['2013', 'october 27', 'new york giants', '15 - 7', 'philadelphia eagles', 'lincoln financial field']]