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2009 - 10 louisville cardinals men 's basketball team

https://en.wikipedia.org/wiki/2009%E2%80%9310_Louisville_Cardinals_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25118909-3.html.csv

majority

the majority of players on the 2009 - 10 louisville cardinals men 's basketball team play the guard position .

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

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

most_eq { all_rows ; position ; guard } = true

for the position records of all rows , most of them fuzzily match to guard .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'position_3': 3, 'guard_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'position_3': 'position', 'guard_4': 'guard'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'position_3': [0], 'guard_4': [0]}

['name', '-', 'position', 'height', 'weight', 'year', 'former school', 'hometown']

[['chris brickley', '11', 'guard', '6 - 4', '175', 'senior', 'northeastern university', 'manchester , nh'], ['rakeem buckles', '4', 'forward', '6 - 8', '200', 'freshman', 'pace', 'miami , fl'], ['reginald delk', '12', 'guard', '6 - 4', '175', 'senior', 'mississippi state university', 'jackson , tn'], ['george goode', '22', 'guard', '6 - 8', '205', 'sophomore', 'raytown south', 'raytown , mo'], ['terrence jennings', '23', 'forward', '6 - 10', '225', 'sophomore', 'notre dame prep', 'sacramento , ca'], ['preston knowles', '2', 'guard', '6 - 1', '170', 'junior', 'george rogers clark', 'winchester , ky'], ['kyle kuric', '14', 'guard', '6 - 4', '175', 'sophomore', 'reitz memorial', 'evansville , in'], ['mike marra', '33', 'guard', '6 - 4', '190', 'freshman', 'northfield mt hermon', 'esmond , ri'], ['samardo samuels', '15', 'forward', '6 - 8', '240', 'sophomore', 'st benedict', 'trelawny , jamaica'], ['peyton siva', '3', 'guard', '5 - 10', '165', 'freshman', 'franklin', 'seattle , wa'], ['jerry smith', '34', 'guard', '6 - 1', '200', 'senior', 'east', 'wauwatosa , wi'], ['edgar sosa', '10', 'guard', '6 - 1', '200', 'senior', 'rice', 'bronx , ny'], ['jared swopshire', '21', 'forward', '6 - 7', '215', 'sophomore', 'img academy', 'st louis , mo'], ['stephan van treese', '44', 'forward', '6 - 8', '220', 'freshman', 'lawrence north', 'indianapolis , in']]

smallville ( season 10 )

https://en.wikipedia.org/wiki/Smallville_%28season_10%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-26464364-1.html.csv

unique

the only episode directed by turi meyer was episode 6 which was called harvest .

{'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2,3', 'criterion': 'equal', 'value': 'turi meyer', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'turi meyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer .', 'tostr': 'filter_eq { all_rows ; directed by ; turi meyer }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; directed by ; turi meyer } }', 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'turi meyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer .', 'tostr': 'filter_eq { all_rows ; directed by ; turi meyer }'}, '-'], 'result': '6', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; directed by ; turi meyer } ; - }'}, '6'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; - } ; 6 }', 'tointer': 'the - record of this unqiue row is 6 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'turi meyer'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer .', 'tostr': 'filter_eq { all_rows ; directed by ; turi meyer }'}, 'title'], 'result': 'harvest', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; directed by ; turi meyer } ; title }'}, 'harvest'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; title } ; harvest }', 'tointer': 'the title record of this unqiue row is harvest .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; - } ; 6 } ; eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; title } ; harvest } }', 'tointer': 'the - record of this unqiue row is 6 . the title record of this unqiue row is harvest .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; directed by ; turi meyer } } ; and { eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; - } ; 6 } ; eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; title } ; harvest } } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to turi meyer . there is only one such row in the table . the - record of this unqiue row is 6 . the title record of this unqiue row is harvest .'}

and { only { filter_eq { all_rows ; directed by ; turi meyer } } ; and { eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; - } ; 6 } ; eq { hop { filter_eq { all_rows ; directed by ; turi meyer } ; title } ; harvest } } } = true

select the rows whose directed by record fuzzily matches to turi meyer . there is only one such row in the table . the - record of this unqiue row is 6 . the title record of this unqiue row is harvest .

10

8

{'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'directed by_10': 10, 'turi meyer_11': 11, 'and_6': 6, 'eq_3': 3, 'num_hop_2': 2, '-_12': 12, '6_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'title_14': 14, 'harvest_15': 15}

{'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'directed by_10': 'directed by', 'turi meyer_11': 'turi meyer', 'and_6': 'and', 'eq_3': 'eq', 'num_hop_2': 'num_hop', '-_12': '-', '6_13': '6', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'title_14': 'title', 'harvest_15': 'harvest'}

{'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'directed by_10': [0], 'turi meyer_11': [0], 'and_6': [7], 'eq_3': [6], 'num_hop_2': [3], '-_12': [2], '6_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'title_14': [4], 'harvest_15': [5]}

['no', '-', 'title', 'directed by', 'written by', 'us air date', 'production code', 'us viewers ( million )']

[['196', '1', 'lazarus', 'kevin g fair', 'don whitehead & holly henderson', 'september 24 , 2010', '3x6001', '2.98'], ['197', '2', 'shield', 'glen winter', 'jordan hawley', 'october 1 , 2010', '3x6002', '2.38'], ['198', '3', 'supergirl', 'mairzee almas', 'anne cofell saunders', 'october 8 , 2010', '3x6003', '2.30'], ['199', '4', 'homecoming', 'jeannot szwarc', 'brian peterson & kelly souders', 'october 15 , 2010', '3x6004', '3.19'], ['200', '5', 'isis', 'james marshall', 'genevieve sparling', 'october 22 , 2010', '3x6005', '2.60'], ['201', '6', 'harvest', 'turi meyer', 'al septien & turi meyer', 'october 29 , 2010', '3x6007', '2.96'], ['202', '7', 'ambush', 'christopher petry', 'don whitehead & holly henderson', 'november 5 , 2010', '3x6006', '2.63'], ['203', '8', 'abandoned', 'kevin g fair', 'drew landis & julia swift', 'november 12 , 2010', '3x6008', '2.90'], ['204', '9', 'patriot', 'tom welling', 'john chisholm', 'november 19 , 2010', '3x6009', '2.60'], ['205', '10', 'luthor', 'kelly souders', 'bryan q miller', 'december 3 , 2010', '3x6010', '2.76'], ['206', '11', 'icarus', 'mairzee almas', 'genevieve sparling', 'december 10 , 2010', '3x6011', '2.55'], ['207', '12', 'collateral', 'morgan beggs', 'jordan hawley', 'february 4 , 2011', '3x6012', '2.37'], ['208', '13', 'beacon', 'mike rohl', 'don whitehead & holly henderson', 'february 11 , 2011', '3x6013', '2.32'], ['209', '14', 'masquerade', 'tim scanlan', 'bryan q miller', 'february 18 , 2011', '3x6014', '2.22'], ['210', '15', 'fortune', 'christopher petry', 'anne coffell saunders', 'february 25 , 2011', '3x6015', '2.56'], ['211', '16', 'scion', 'al septien', 'al septien & turi meyer', 'march 4 , 2011', '3x6016', '2.18'], ['212', '17', 'kent', 'jeannot szwarc', 'brian peterson & kelly souders', 'april 15 , 2011', '3x6018', '2.37'], ['213', '18', 'booster', 'tom welling', 'geoff johns', 'april 22 , 2011', '3x6017', '2.35'], ['214', '19', 'dominion', 'justin hartley', 'john chisholm', 'april 29 , 2011', '3x6021', '1.99']]

1991 - 92 in argentine football

https://en.wikipedia.org/wiki/1991%E2%80%9392_in_Argentine_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-14390413-1.html.csv

superlative

the river plate team had the most points in the 1991 - 92 argentine football season .

{'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', 'points'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; points }'}, 'team'], 'result': 'river plate', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; points } ; team }'}, 'river plate'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; points } ; team } ; river plate } = true', 'tointer': 'select the row whose points record of all rows is maximum . the team record of this row is river plate .'}

eq { hop { argmax { all_rows ; points } ; team } ; river plate } = true

select the row whose points record of all rows is maximum . the team record of this row is river plate .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'points_5': 5, 'team_6': 6, 'river plate_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'points_5': 'points', 'team_6': 'team', 'river plate_7': 'river plate'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'points_5': [0], 'team_6': [1], 'river plate_7': [2]}

['team', 'average', 'points', 'played', '1989 - 90', '1990 - 91', '1991 - 1992']

[['river plate', '1.342', '153', '114', '53', '45', '55'], ['boca juniors', '1.263', '144', '114', '43', '51', '50'], ['vélez sársfield', '1.184', '135', '114', '42', '45', '48'], ["newell 's old boys", '1.123', '128', '114', '36', '48', '44'], ['independiente', '1.070', '122', '114', '46', '40', '36'], ['racing club', '1.035', '118', '114', '39', '40', '39'], ['huracán', '1.026', '78', '76', 'n / a', '40', '38'], ['rosario central', '1.018', '116', '114', '43', '39', '34'], ['ferro carril oeste', '1.000', '114', '114', '39', '38', '37'], ['san lorenzo', '1.000', '114', '114', '35', '45', '34'], ['gimnasia de la plata', '0.991', '113', '114', '39', '33', '41'], ['platense', '0.991', '113', '114', '36', '35', '42'], ['argentinos juniors', '0.956', '109', '114', '38', '36', '35'], ['deportivo mandiyú', '0.939', '107', '114', '36', '38', '33'], ['belgrano de córdoba', '0.921', '35', '38', 'n / a', 'n / a', '35'], ['deportivo español', '0.912', '104', '114', '31', '28', '45'], ['estudiantes de la plata', '0.895', '102', '114', '34', '39', '29'], ['talleres de córdoba', '0.895', '102', '114', '36', '29', '37'], ['unión de santa fe', '0.825', '94', '114', '36', '31', '27']]

2008 detroit shock season

https://en.wikipedia.org/wiki/2008_Detroit_Shock_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17103729-10.html.csv

majority

all games of the detroit shock 's in the 2008 season were played in the month of september .

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

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

all_eq { all_rows ; date ; september } = true

for the date records of all rows , all of them fuzzily match to september .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, 'september_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', 'september_4': 'september'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], 'september_4': [0]}

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

[['30', 'september 5', 'indiana', '90 - 68', 'pierson ( 20 )', 'pierson ( 6 )', 'mcwilliams - franklin , pierson ( 4 )', 'palace of auburn hills 9287', '18 - 12'], ['31', 'september 6', 'washington', '84 - 69', 'mcwilliams - franklin ( 21 )', 'nolan ( 10 )', 'smith ( 8 )', 'verizon center 9976', '19 - 12'], ['32', 'september 9', 'phoenix', '89 - 78', 'nolan ( 18 )', 'braxton , hornbuckle , mcwilliams - franklin ( 8 )', 'pierson , smith ( 5 )', 'palace of auburn hills 7495', '20 - 12'], ['33', 'september 11', 'washington', '78 - 66', 'nolan ( 17 )', 'mcwilliams - franklin ( 8 )', 'smith ( 6 )', 'palace of auburn hills 8145', '21 - 12'], ['34', 'september 14', 'new york', '61 - 59', 'nolan , pierson ( 11 )', 'hornbuckle , nolan ( 7 )', 'powell ( 4 )', 'madison square garden 10042', '22 - 12']]

united states house of representatives elections , 2006

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_2006

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1805191-4.html.csv

aggregation

the arizona incumbents in the 2006 united states house of representatives elections had an average first election year of 1996 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '1996', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'first elected'], 'result': '1996', 'ind': 0, 'tostr': 'avg { all_rows ; first elected }'}, '1996'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; first elected } ; 1996 } = true', 'tointer': 'the average of the first elected record of all rows is 1996 .'}

round_eq { avg { all_rows ; first elected } ; 1996 } = true

the average of the first elected record of all rows is 1996 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'first elected_4': 4, '1996_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'first elected_4': 'first elected', '1996_5': '1996'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'first elected_4': [0], '1996_5': [1]}

['district', 'incumbent', 'party', 'first elected', 'results']

[['arizona 1', 'rick renzi', 'republican', '2002', 're - elected'], ['arizona 2', 'trent franks', 'republican', '2002', 're - elected'], ['arizona 3', 'john shadegg', 'republican', '1994', 're - elected'], ['arizona 4', 'ed pastor', 'democratic', '1990', 're - elected'], ['arizona 5', 'j d hayworth', 'republican', '1994', 'lost re - election democratic gain'], ['arizona 6', 'jeff flake', 'republican', '2000', 're - elected'], ['arizona 7', 'raul grijalva', 'democratic', '2002', 're - elected'], ['arizona 8', 'jim kolbe', 'republican', '1984', 'retired democratic gain']]

you can dance : po prostu tańcz !

https://en.wikipedia.org/wiki/You_Can_Dance%3A_Po_prostu_ta%C5%84cz%21

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17671150-9.html.csv

aggregation

on you can dance : po prostu tancz ! the total points were 235 .

{'scope': 'all', 'col': '4', 'type': 'sum', 'result': '235', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'points jury'], 'result': '235', 'ind': 0, 'tostr': 'sum { all_rows ; points jury }'}, '235'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; points jury } ; 235 } = true', 'tointer': 'the sum of the points jury record of all rows is 235 .'}

round_eq { sum { all_rows ; points jury } ; 235 } = true

the sum of the points jury record of all rows is 235 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'points jury_4': 4, '235_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'points jury_4': 'points jury', '235_5': '235'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'points jury_4': [0], '235_5': [1]}

['team', 'dance', 'music', 'points jury', 'place']

[['rafał bryndal & diana staniszewska', 'jive', 'i get around - beach boys', '18 ( 5 , 5 , 4 , 4 )', '4 . place'], ['rafał bryndal & diana staniszewska', 'pop', 'thriller - michael jackson', '31 ( 5 , 6 , 10 , 10 )', '4 . place'], ['anna guzik & rafał kamiński', 'tango', 'libertango - ástor piazzolla', '24 ( 7 , 5 , 6 , 6 )', '1 . place'], ['anna guzik & rafał kamiński', 'hip - hop', 'yeah - usher', '39 ( 9 , 10 , 10 , 10 )', '1 . place'], ['mateusz damięcki & anna bosak', 'waltz', 'imagine - john lennon', '34 ( 7 , 8 , 9 , 10 )', '2 . place'], ['mateusz damięcki & anna bosak', 'jazz', "when you 're gone - avril lavigne", '33 ( 8 , 10 , 7 , 8 )', '2 . place'], ['justyna steczkowska & maciej florek', 'tango', "et si tu n'existais pas - toto cutugno & delanoë", '17 ( 4 , 5 , 5 , 3 )', '3 . place'], ['justyna steczkowska & maciej florek', 'modern', 'bring me to life - evanescence', '39 ( 9 , 10 , 10 , 10 )', '3 . place']]

1933 vfl season

https://en.wikipedia.org/wiki/1933_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10790397-11.html.csv

ordinal

princes park venue recorded the highest crowd participation during the 1933 vfl season .

{'row': '3', 'col': '6', 'order': '1', 'col_other': '5', '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', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'princes park', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'princes park'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; princes park } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is princes park .'}

eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; princes park } = true

select the row whose crowd record of all rows is 1st maximum . the venue record of this row is princes park .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'princes park_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', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'princes park_8': 'princes park'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'princes park_8': [2]}

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

[['north melbourne', '13.12 ( 90 )', 'south melbourne', '15.13 ( 103 )', 'arden street oval', '15000', '8 july 1933'], ['collingwood', '20.19 ( 139 )', 'essendon', '14.14 ( 98 )', 'victoria park', '8500', '8 july 1933'], ['carlton', '10.10 ( 70 )', 'richmond', '9.13 ( 67 )', 'princes park', '43000', '8 july 1933'], ['melbourne', '21.10 ( 136 )', 'hawthorn', '15.8 ( 98 )', 'mcg', '6877', '8 july 1933'], ['st kilda', '11.14 ( 80 )', 'geelong', '7.13 ( 55 )', 'junction oval', '10000', '8 july 1933'], ['footscray', '15.6 ( 96 )', 'fitzroy', '8.14 ( 62 )', 'western oval', '18000', '8 july 1933']]

1988 open championship

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18139254-4.html.csv

unique

seve ballesteros was the only player from spain in the 1988 open championship .

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

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

and { only { filter_eq { all_rows ; country ; spain } } ; eq { hop { filter_eq { all_rows ; country ; spain } ; player } ; seve ballesteros } } = true

select the rows whose country record fuzzily matches to spain . there is only one such row in the table . the player record of this unqiue row is seve ballesteros .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'country_7': 7, 'spain_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'player_9': 9, 'seve ballesteros_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'country_7': 'country', 'spain_8': 'spain', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'player_9': 'player', 'seve ballesteros_10': 'seve ballesteros'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'country_7': [0], 'spain_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'player_9': [2], 'seve ballesteros_10': [3]}

['place', 'player', 'country', 'score', 'to par']

[['1', 'seve ballesteros', 'spain', '67', '4'], ['t2', 'brad faxon', 'united states', '69', '2'], ['t2', 'wayne grady', 'australia', '69', '2'], ['t4', 'don pooley', 'united states', '70', '1'], ['t4', 'nick price', 'zimbabwe', '70', '1'], ['t4', 'noel ratcliffe', 'australia', '70', '1'], ['t4', 'peter senior', 'australia', '70', '1'], ['t8', 'andy bean', 'united states', '71', 'e'], ['t8', 'bob charles', 'new zealand', '71', 'e'], ['t8', 'howard clark', 'england', '71', 'e'], ['t8', 'nick faldo', 'england', '71', 'e'], ['t8', 'david frost', 'south africa', '71', 'e'], ['t8', 'jay haas', 'united states', '71', 'e'], ['t8', 'mark james', 'england', '71', 'e'], ['t8', 'gary koch', 'united states', '71', 'e'], ['t8', 'david j russell', 'england', '71', 'e'], ['t8', 'andrew sherborne', 'england', '71', 'e'], ['t8', 'bob tway', 'united states', '71', 'e']]

list of superfund sites in illinois

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12769819-1.html.csv

ordinal

of the superfund sites in illinois , the one that has the third-latest list date is in lake county .

{'row': '9', 'col': '3', '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', 'listed', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; listed ; 3 }'}, 'county'], 'result': 'lake', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; listed ; 3 } ; county }'}, 'lake'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; listed ; 3 } ; county } ; lake } = true', 'tointer': 'select the row whose listed record of all rows is 3rd maximum . the county record of this row is lake .'}

eq { hop { nth_argmax { all_rows ; listed ; 3 } ; county } ; lake } = true

select the row whose listed record of all rows is 3rd maximum . the county record of this row is lake .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'listed_5': 5, '3_6': 6, 'county_7': 7, 'lake_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', 'listed_5': 'listed', '3_6': '3', 'county_7': 'county', 'lake_8': 'lake'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'listed_5': [0], '3_6': [0], 'county_7': [1], 'lake_8': [2]}

['cerclis id', 'county', 'listed', 'construction completed', 'partially deleted', 'deleted']

[['ild980607055', 'adams', '08 / 30 / 1990', '03 / 31 / 1999', 'n / a', 'n / a'], ['ild980996789', 'alexander', '10 / 04 / 1989', '09 / 28 / 1999', 'n / a', '01 / 08 / 2001'], ['ild980397079', 'cumberland', '09 / 08 / 1983', '09 / 24 / 1992', 'n / a', 'n / a'], ['il3210020803', 'jo daviess', '03 / 13 / 1989', 'n / a', 'n / a', 'n / a'], ['ild000802827', 'lake', '09 / 08 / 1983', 'n / a', 'n / a', 'n / a'], ['ild003817137', 'lake', '06 / 10 / 1986', '09 / 12 / 1989', 'n / a', '02 / 11 / 1991'], ['ild005443544', 'lake', '09 / 08 / 1983', '12 / 31 / 1991', 'n / a', 'n / a'], ['ild980500102', 'lake', '03 / 31 / 1989', '09 / 23 / 2005', 'n / a', 'n / a'], ['ild980605836', 'lake', '02 / 21 / 1990', '06 / 29 / 2001', 'n / a', 'n / a'], ['ild048843809', 'madison', '03 / 04 / 2010', '-', '-', '-'], ['il0210090049', 'will', '03 / 13 / 1989', '09 / 29 / 2008', 'n / a', 'n / a'], ['il7213820460', 'will', '07 / 22 / 1987', '09 / 10 / 2008', 'n / a', 'n / a'], ['ild053219259', 'winnebago', '09 / 08 / 1983', '07 / 13 / 1998', 'n / a', 'n / a']]

yen plus

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18685750-2.html.csv

ordinal

' time and again ' was the second latest manwha in the yen plus to have its first issue created .

{'row': '6', 'col': '3', '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', 'first issue', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; first issue ; 2 }'}, 'title'], 'result': 'time and again', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; first issue ; 2 } ; title }'}, 'time and again'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; first issue ; 2 } ; title } ; time and again } = true', 'tointer': 'select the row whose first issue record of all rows is 2nd maximum . the title record of this row is time and again .'}

eq { hop { nth_argmax { all_rows ; first issue ; 2 } ; title } ; time and again } = true

select the row whose first issue record of all rows is 2nd maximum . the title record of this row is time and again .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'first issue_5': 5, '2_6': 6, 'title_7': 7, 'time and again_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', 'first issue_5': 'first issue', '2_6': '2', 'title_7': 'title', 'time and again_8': 'time and again'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'first issue_5': [0], '2_6': [0], 'title_7': [1], 'time and again_8': [2]}

['title', 'author', 'first issue', 'last issue', 'completed']

[["aron 's absurd armada", 'misun kim', 'august 2010', 'ongoing', 'no'], ['jack frost', 'jinho ko', 'august 2008', 'ongoing', 'no'], ['one fine day', 'sirial', 'august 2008', 'july 2010', 'yes'], ['pig bride', 'kookhwa huh ( author ) , sujin kim ( artist )', 'august 2008', 'july 2010', 'yes'], ['sarasah', 'ryang ruy', 'august 2008', 'june 2009', 'no'], ['time and again', 'jiun yun', 'february 2009', 'ongoing', 'no']]

2008 - 09 temple owls men 's basketball team

https://en.wikipedia.org/wiki/2008%E2%80%9309_Temple_Owls_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-30054758-3.html.csv

unique

the december 6 game was the only game played at the bryce jordan center .

{'scope': 'all', 'row': '2', 'col': '8', 'col_other': '2', 'criterion': 'equal', 'value': 'bryce jordan center , state college , pa ( 9833 )', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'bryce jordan center , state college , pa ( 9833 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) .', 'tostr': 'filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } }', 'tointer': 'select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location attendance', 'bryce jordan center , state college , pa ( 9833 )'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) .', 'tostr': 'filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) }'}, 'date'], 'result': 'december 6', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date }'}, 'december 6'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date } ; december 6 }', 'tointer': 'the date record of this unqiue row is december 6 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } } ; eq { hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date } ; december 6 } } = true', 'tointer': 'select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) . there is only one such row in the table . the date record of this unqiue row is december 6 .'}

and { only { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } } ; eq { hop { filter_eq { all_rows ; location attendance ; bryce jordan center , state college , pa ( 9833 ) } ; date } ; december 6 } } = true

select the rows whose location attendance record fuzzily matches to bryce jordan center , state college , pa ( 9833 ) . there is only one such row in the table . the date record of this unqiue row is december 6 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location attendance_7': 7, 'bryce jordan center , state college , pa (9833)_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, 'december 6_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location attendance_7': 'location attendance', 'bryce jordan center , state college , pa (9833)_8': 'bryce jordan center , state college , pa ( 9833 )', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', 'december 6_10': 'december 6'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location attendance_7': [0], 'bryce jordan center , state college , pa (9833)_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], 'december 6_10': [3]}

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

[['6', 'december 3', 'miami ( oh )', 'l 68 - 52', 'sergio olmos - 12', 'brooks - 6', 'inge - 5', 'liacouras center , philadelphia , pa ( 5029 )', '3 - 3'], ['7', 'december 6', 'penn state', 'w 65 - 59', 'inge - 19', 'allen - 10', 'inge - 6', 'bryce jordan center , state college , pa ( 9833 )', '4 - 3'], ['8', 'december 13', '8 tennessee', 'w 88 - 72', 'christmas - 35', 'brooks - 10', 'inge - 4', 'liacouras center , philadelphia , pa ( 8068 )', '5 - 3'], ['9', 'december 20', 'kansas', 'l 71 - 59', 'christmas - 21', 'allen - 7', 'allen - 5', 'phog allen fieldhouse , lawrence , ks ( 16300 )', '5 - 4'], ['10', 'december 22', 'long beach state', 'l 76 - 71', 'christmas - 19', 'allen - 11', 'allen - 5', 'walter pyramid , long beach , ca ( 2042 )', '5 - 5']]

list of widows and widowers

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-24143253-4.html.csv

unique

norris church mailer and norman mailer were the only widow and widowers with 1 son .

{'scope': 'all', 'row': '5', 'col': '6', 'col_other': '1,2', 'criterion': 'equal', 'value': '1 son', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'children together', '1 son'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose children together record fuzzily matches to 1 son .', 'tostr': 'filter_eq { all_rows ; children together ; 1 son }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; children together ; 1 son } }', 'tointer': 'select the rows whose children together record fuzzily matches to 1 son . there is only one such row in the table .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'children together', '1 son'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose children together record fuzzily matches to 1 son .', 'tostr': 'filter_eq { all_rows ; children together ; 1 son }'}, 'name'], 'result': 'norris church mailer', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; children together ; 1 son } ; name }'}, 'norris church mailer'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; children together ; 1 son } ; name } ; norris church mailer }', 'tointer': 'the name record of this unqiue row is norris church mailer .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'children together', '1 son'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose children together record fuzzily matches to 1 son .', 'tostr': 'filter_eq { all_rows ; children together ; 1 son }'}, 'deceased spouse'], 'result': 'norman mailer', 'ind': 4, 'tostr': 'hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse }'}, 'norman mailer'], 'result': True, 'ind': 5, 'tostr': 'eq { hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse } ; norman mailer }', 'tointer': 'the deceased spouse record of this unqiue row is norman mailer .'}], 'result': True, 'ind': 6, 'tostr': 'and { eq { hop { filter_eq { all_rows ; children together ; 1 son } ; name } ; norris church mailer } ; eq { hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse } ; norman mailer } }', 'tointer': 'the name record of this unqiue row is norris church mailer . the deceased spouse record of this unqiue row is norman mailer .'}], 'result': True, 'ind': 7, 'tostr': 'and { only { filter_eq { all_rows ; children together ; 1 son } } ; and { eq { hop { filter_eq { all_rows ; children together ; 1 son } ; name } ; norris church mailer } ; eq { hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse } ; norman mailer } } } = true', 'tointer': 'select the rows whose children together record fuzzily matches to 1 son . there is only one such row in the table . the name record of this unqiue row is norris church mailer . the deceased spouse record of this unqiue row is norman mailer .'}

and { only { filter_eq { all_rows ; children together ; 1 son } } ; and { eq { hop { filter_eq { all_rows ; children together ; 1 son } ; name } ; norris church mailer } ; eq { hop { filter_eq { all_rows ; children together ; 1 son } ; deceased spouse } ; norman mailer } } } = true

select the rows whose children together record fuzzily matches to 1 son . there is only one such row in the table . the name record of this unqiue row is norris church mailer . the deceased spouse record of this unqiue row is norman mailer .

10

8

{'and_7': 7, 'result_8': 8, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_9': 9, 'children together_10': 10, '1 son_11': 11, 'and_6': 6, 'str_eq_3': 3, 'str_hop_2': 2, 'name_12': 12, 'norris church mailer_13': 13, 'str_eq_5': 5, 'str_hop_4': 4, 'deceased spouse_14': 14, 'norman mailer_15': 15}

{'and_7': 'and', 'result_8': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_9': 'all_rows', 'children together_10': 'children together', '1 son_11': '1 son', 'and_6': 'and', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'name_12': 'name', 'norris church mailer_13': 'norris church mailer', 'str_eq_5': 'str_eq', 'str_hop_4': 'str_hop', 'deceased spouse_14': 'deceased spouse', 'norman mailer_15': 'norman mailer'}

{'and_7': [8], 'result_8': [], 'only_1': [7], 'filter_str_eq_0': [1, 2, 4], 'all_rows_9': [0], 'children together_10': [0], '1 son_11': [0], 'and_6': [7], 'str_eq_3': [6], 'str_hop_2': [3], 'name_12': [2], 'norris church mailer_13': [3], 'str_eq_5': [6], 'str_hop_4': [5], 'deceased spouse_14': [4], 'norman mailer_15': [5]}

['name', 'deceased spouse', 'cause of death', 'date of spouses death', 'length of marriage', 'children together', 'current marital status']

[['samuel beckett', 'suzanne dãchevaux - dumesnil', 'unknown', 'july 17 , 1989 ( aged89 )', '28 years', 'none', 'deceased ( 1989 )'], ['jan berenstain', 'stan berenstain', 'unknown', 'november 26 , 2005 ( aged82 )', '59 years', '2 sons ( leo , michael )', 'deceased ( 2012 )'], ['ray bradbury', 'marguerite mcclure', 'not known', 'november 24 , 2003 ( aged81 )', '56 years', '4 daughters ( susan , ramona , bettina , alexandra )', 'deceased ( 2012 )'], ['mary welsh hemingway', 'ernest hemingway', 'suicide', 'july 2 , 1961 ( aged61 )', '15 years', 'none ( miscarriage )', 'deceased ( 1986 )'], ['norris church mailer', 'norman mailer', 'acute renal failure', 'november 10 , 2007 ( aged84 )', '27 years', '1 son ( john )', 'deceased ( 2010 )'], ['frederica sagor maas', 'ernest maas', 'natural causes', 'july 21 , 1986 ( aged94 )', '59 years', 'none', 'deceased ( 2012 )'], ['edgar allan poe', 'virginia eliza clemm poe', 'tuberculosis', 'january 30 , 1847 ( aged24 )', '11 years', 'none', 'deceased ( 1849 )'], ['dr seuss', 'helen palmer geisel', 'overdose of barbiturates', 'october 23 , 1967 ( aged68 )', '40 years', 'none', 'deceased ( 1991 )'], ['robert treuhaft', 'jessica mitford', 'lung cancer', 'july 22 , 1996 ( aged78 )', '53 years', '2 sons ( nicholas , benjamin )', 'deceased ( 2001 )']]

1953 washington redskins season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15123292-1.html.csv

aggregation

the average crowd attendance in the 1953 washington redskins season was 24652 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '24652', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '24652', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '24652'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 24652 } = true', 'tointer': 'the average of the attendance record of all rows is 24652 .'}

round_eq { avg { all_rows ; attendance } ; 24652 } = true

the average of the attendance record of all rows is 24652 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '24652_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '24652_5': '24652'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '24652_5': [1]}

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

[['1', 'september 27 , 1953', 'chicago cardinals', 'w 24 - 13', '16055'], ['2', 'october 2 , 1953', 'philadelphia eagles', 't 21 - 21', '19099'], ['3', 'october 11 , 1953', 'new york giants', 'w 13 - 9', '26241'], ['4', 'october 18 , 1953', 'cleveland browns', 'l 30 - 14', '33963'], ['5', 'october 25 , 1953', 'baltimore colts', 'l 27 - 17', '34031'], ['6', 'november 1 , 1953', 'cleveland browns', 'l 27 - 3', '47845'], ['7', 'november 8 , 1953', 'chicago cardinals', 'w 28 - 17', '19654'], ['8', 'november 15 , 1953', 'chicago bears', 'l 27 - 24', '21392'], ['9', 'november 22 , 1953', 'new york giants', 'w 24 - 21', '16887'], ['10', 'november 29 , 1953', 'pittsburgh steelers', 'w 17 - 9', '17026'], ['11', 'december 6 , 1953', 'philadelphia eagles', 'w 10 - 0', '21579'], ['12', 'december 13 , 1953', 'pittsburgh steelers', 'l 14 - 13', '22057']]

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

aggregation

the total sum of enrollments among the five institutions participating in the kingco athletic conference was 6339 individuals .

{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '6339', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'enrollment'], 'result': '6339', 'ind': 0, 'tostr': 'sum { all_rows ; enrollment }'}, '6339'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; enrollment } ; 6339 } = true', 'tointer': 'the sum of the enrollment record of all rows is 6339 .'}

round_eq { sum { all_rows ; enrollment } ; 6339 } = true

the sum of the enrollment record of all rows is 6339 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'enrollment_4': 4, '6339_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'enrollment_4': 'enrollment', '6339_5': '6339'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'enrollment_4': [0], '6339_5': [1]}

['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']]

concrete canoe

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2331549-1.html.csv

ordinal

the 2nd to last y ear for concrete canoe was when the host city was seattle , washington .

{'row': '19', 'col': '1', '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', 'year', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; year ; 2 }'}, 'host city'], 'result': 'seattle , washington', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; year ; 2 } ; host city }'}, 'seattle , washington'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; year ; 2 } ; host city } ; seattle , washington } = true', 'tointer': 'select the row whose year record of all rows is 2nd maximum . the host city record of this row is seattle , washington .'}

eq { hop { nth_argmax { all_rows ; year ; 2 } ; host city } ; seattle , washington } = true

select the row whose year record of all rows is 2nd maximum . the host city record of this row is seattle , washington .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'year_5': 5, '2_6': 6, 'host city_7': 7, 'seattle , washington_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', 'year_5': 'year', '2_6': '2', 'host city_7': 'host city', 'seattle , washington_8': 'seattle , washington'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'year_5': [0], '2_6': [0], 'host city_7': [1], 'seattle , washington_8': [2]}

['year', 'host city', 'host school', 'champion', 'second place', 'third place']

[['1988', 'east lansing , michigan', 'michigan state university', 'university of california , berkeley', 'university of new hampshire', 'university of akron'], ['1989', 'lubbock , texas', 'texas tech university', 'university of california , berkeley', 'michigan state university', 'university of new hampshire'], ['1990', 'buffalo , new york', 'state university of new york', 'michigan state university', 'university of maryland', 'university of california , berkeley'], ['1991', 'orlando , florida', 'university of central florida', 'university of california , berkeley', 'university of maryland', 'university at buffalo'], ['1992', 'fort collins , colorado', 'colorado state university', 'university of california , berkeley', 'university of alabama , huntsville', 'university of new orleans'], ['1993', 'sacramento , california', 'california state university , sacramento', 'university of alabama , huntsville', 'michigan state university', 'university of california , berkeley'], ['1994', 'new orleans , louisiana', 'university of new orleans', 'university of alabama , huntsville', 'university of california , berkeley', 'university of new orleans'], ['1995', 'washington , dc', 'george washington university', 'south dakota school of mines & technology', 'california state university , sacramento', 'michigan state university'], ['1996', 'madison , wisconsin', 'university of wisconsin at madison', 'university of alabama , huntsville', 'michigan state university', 'university of california , berkeley'], ['1997', 'cleveland , ohio', 'cleveland state university', 'florida institute of technology', 'university of alabama , huntsville', 'university of california , berkeley'], ['1998', 'rapid city , south dakota', 'south dakota school of mines & technology', 'university of alabama , huntsville', 'california state university , sacramento', 'clemson university'], ['1999', 'melbourne , florida', 'florida institute of technology', 'clemson university', 'university of alabama , huntsville', 'oklahoma state university'], ['2000', 'golden , colorado', 'colorado school of mines', 'clemson university', 'oklahoma state university', 'florida institute of technology'], ['2001', 'san diego , california', 'san diego state university', 'university of alabama , huntsville', 'clemson university', 'oklahoma state university'], ['2002', 'madison , wisconsin', 'university of wisconsin', 'clemson university', 'université laval', 'oklahoma state university'], ['2003', 'philadelphia , pennsylvania', 'drexel university', 'university of wisconsin , madison', 'université laval', 'university of california , berkeley'], ['2004', 'washington , dc', 'the catholic university of america', 'university of wisconsin , madison', 'université laval', 'university of alabama , huntsville'], ['2005', 'clemson , south carolina', 'clemson university', 'university of wisconsin , madison', 'clemson university', 'michigan technological university'], ['2007', 'seattle , washington', 'university of washington', 'university of wisconsin , madison', 'university of florida', 'university of nevada , reno'], ['2008', 'montreal , quebec', 'école de technologie supérieure', 'university of nevada , reno', 'university of california , berkeley', 'école de technologie supérieure']]

1972 - 73 philadelphia flyers season

https://en.wikipedia.org/wiki/1972%E2%80%9373_Philadelphia_Flyers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14294324-15.html.csv

majority

all of the players that were drafted in the 1972-73 philadelphia flyers ' season were from canada .

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

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

most_eq { all_rows ; nationality ; canada } = true

for the nationality records of all rows , most of them fuzzily match to canada .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'nationality_3': 3, 'canada_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'nationality_3': 'nationality', 'canada_4': 'canada'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'nationality_3': [0], 'canada_4': [0]}

['round', 'player', 'position', 'nationality', 'college / junior / club team ( league )']

[['1', 'bill barber', 'left wing', 'canada', 'kitchener rangers ( oha )'], ['2', 'tom bladon', 'defense', 'canada', 'edmonton oil kings ( wchl )'], ['3', 'jim watson', 'defense', 'canada', 'calgary centennials ( wchl )'], ['4', 'al macadam', 'right wing', 'canada', 'charlottetown islanders ( mjhl )'], ['5', 'darryl fedorak', 'goaltender', 'canada', 'victoria cougars ( wchl )'], ['6', 'dave hastings', 'goaltender', 'canada', 'charlottetown islanders ( mjhl )'], ['7', 'serge beaudoin', 'defense', 'canada', 'trois - riviã ¨ res ducs ( qmjhl )'], ['8', 'pat russell', 'right wing', 'canada', 'vancouver nats ( wchl )'], ['9', 'ray boutin', 'goaltender', 'canada', 'sorel black hawks ( qmjhl )']]

1991 - 92 segunda división

https://en.wikipedia.org/wiki/1991%E2%80%9392_Segunda_Divisi%C3%B3n

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12097374-2.html.csv

unique

ce sabadell fc was the only team in the 1991-92 segunda division that had a goal difference of -1 .

{'scope': 'all', 'row': '9', 'col': '10', 'col_other': '2', 'criterion': 'equal', 'value': '-1', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goal difference', '-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal difference record is equal to -1 .', 'tostr': 'filter_eq { all_rows ; goal difference ; -1 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; goal difference ; -1 } }', 'tointer': 'select the rows whose goal difference record is equal to -1 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'goal difference', '-1'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal difference record is equal to -1 .', 'tostr': 'filter_eq { all_rows ; goal difference ; -1 }'}, 'club'], 'result': 'ce sabadell fc', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; goal difference ; -1 } ; club }'}, 'ce sabadell fc'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; goal difference ; -1 } ; club } ; ce sabadell fc }', 'tointer': 'the club record of this unqiue row is ce sabadell fc .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; goal difference ; -1 } } ; eq { hop { filter_eq { all_rows ; goal difference ; -1 } ; club } ; ce sabadell fc } } = true', 'tointer': 'select the rows whose goal difference record is equal to -1 . there is only one such row in the table . the club record of this unqiue row is ce sabadell fc .'}

and { only { filter_eq { all_rows ; goal difference ; -1 } } ; eq { hop { filter_eq { all_rows ; goal difference ; -1 } ; club } ; ce sabadell fc } } = true

select the rows whose goal difference record is equal to -1 . there is only one such row in the table . the club record of this unqiue row is ce sabadell fc .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'goal difference_7': 7, '-1_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'club_9': 9, 'ce sabadell fc_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'goal difference_7': 'goal difference', '-1_8': '-1', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'club_9': 'club', 'ce sabadell fc_10': 'ce sabadell fc'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'goal difference_7': [0], '-1_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'club_9': [2], 'ce sabadell fc_10': [3]}

['position', 'club', 'played', 'points', 'wins', 'draws', 'losses', 'goals for', 'goals against', 'goal difference']

[['1', 'celta de vigo', '38', '53 + 15', '22', '9', '7', '61', '26', '+ 35'], ['2', 'rayo vallecano', '38', '48 + 10', '20', '8', '10', '52', '27', '+ 25'], ['3', 'ue figueres', '38', '47 + 9', '16', '15', '7', '43', '27', '+ 16'], ['4', 'real betis', '38', '46 + 8', '18', '10', '10', '54', '43', '+ 11'], ['5', 'ue lleida', '38', '43 + 5', '17', '9', '12', '52', '36', '+ 16'], ['6', 'barcelona b', '38', '41 + 3', '17', '7', '14', '59', '53', '+ 6'], ['7', 'cp mérida', '38', '41 + 3', '16', '9', '13', '58', '48', '+ 10'], ['8', 'sd compostela', '38', '41 + 3', '15', '11', '12', '36', '32', '+ 4'], ['9', 'ce sabadell fc', '38', '38', '16', '6', '16', '34', '35', '- 1'], ['10', 'racing de santander', '38', '37 - 1', '15', '7', '16', '39', '44', '- 5'], ['11', 'real murcia 1', '38', '36 - 2', '11', '14', '13', '32', '36', '- 4'], ['12', 'sd eibar', '38', '36 - 2', '11', '14', '13', '19', '22', '- 3'], ['13', 'bilbao athletic', '38', '35 - 3', '12', '11', '15', '36', '40', '- 4'], ['14', 'palamós cf', '38', '35 - 3', '13', '9', '16', '39', '46', '- 7'], ['15', 'cd castellón', '38', '35 - 3', '13', '9', '16', '42', '48', '- 6'], ['16', 'real madrid b', '38', '34 - 4', '11', '12', '15', '44', '55', '- 11'], ['17', 'sestao 1', '38', '32 - 6', '11', '10', '17', '26', '44', '- 18'], ['18', 'cd málaga 2', '38', '30 - 8', '10', '10', '18', '25', '45', '- 20'], ['19', 'real avilés', '38', '27 - 11', '9', '9', '20', '31', '56', '- 25'], ['20', 'ud las palmas', '38', '25 - 13', '8', '9', '21', '39', '58', '- 19']]

list of free multiplayer online games

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17493675-2.html.csv

majority

all of the free multiplayer online games are available on the windows operating system .

{'scope': 'all', 'col': '3', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': 'windows', 'subset': None}

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

all_eq { all_rows ; required os ; windows } = true

for the required os records of all rows , all of them fuzzily match to windows .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'required os_3': 3, 'windows_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'required os_3': 'required os', 'windows_4': 'windows'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'required os_3': [0], 'windows_4': [0]}

['developer ( s )', 'release date', 'required os', 'genre', 'type']

[['robot entertainment , gas powered games', 'august 16 , 2011', 'windows', 'mmorts', '3d'], ['ea games', '2009', 'windows', 'first - person shooter', '3d'], ['stunlock studios', '2011', 'windows', 'moba', '3d'], ['thq', '2010 - 2011', 'windows', 'real - time strategy', '3d'], ['novel , inc', '2011', 'windows', 'mmorpg', '2d'], ['masthead studios', '2013', 'windows', 'third - person shooter', '3d'], ['riot games', '2008 - 2011', 'windows , os x', 'moba', '3d'], ['valve corporation', '2007', 'windows , os x , linux', 'first - person shooter', '3d']]

utah jazz all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11545282-4.html.csv

ordinal

john drew is the third newest member on the utah jazz all - time roster , joining in 1982 .

{'row': '7', 'col': '5', 'order': '3', 'col_other': '1', 'max_or_min': 'max_to_min', 'value_mentioned': 'yes', 'scope': 'all', 'subset': None}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_max', 'args': ['all_rows', 'years for jazz', '3'], 'result': '1982 - 85', 'ind': 0, 'tostr': 'nth_max { all_rows ; years for jazz ; 3 }', 'tointer': 'the 3rd maximum years for jazz record of all rows is 1982 - 85 .'}, '1982 - 85'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_max { all_rows ; years for jazz ; 3 } ; 1982 - 85 }', 'tointer': 'the 3rd maximum years for jazz record of all rows is 1982 - 85 .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmax', 'args': ['all_rows', 'years for jazz', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmax { all_rows ; years for jazz ; 3 }'}, 'player'], 'result': 'john drew', 'ind': 3, 'tostr': 'hop { nth_argmax { all_rows ; years for jazz ; 3 } ; player }'}, 'john drew'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmax { all_rows ; years for jazz ; 3 } ; player } ; john drew }', 'tointer': 'the player record of the row with 3rd maximum years for jazz record is john drew .'}], 'result': True, 'ind': 5, 'tostr': 'and { eq { nth_max { all_rows ; years for jazz ; 3 } ; 1982 - 85 } ; eq { hop { nth_argmax { all_rows ; years for jazz ; 3 } ; player } ; john drew } } = true', 'tointer': 'the 3rd maximum years for jazz record of all rows is 1982 - 85 . the player record of the row with 3rd maximum years for jazz record is john drew .'}

and { eq { nth_max { all_rows ; years for jazz ; 3 } ; 1982 - 85 } ; eq { hop { nth_argmax { all_rows ; years for jazz ; 3 } ; player } ; john drew } } = true

the 3rd maximum years for jazz record of all rows is 1982 - 85 . the player record of the row with 3rd maximum years for jazz record is john drew .

6

6

{'and_5': 5, 'result_6': 6, 'eq_1': 1, 'nth_max_0': 0, 'all_rows_7': 7, 'years for jazz_8': 8, '3_9': 9, '1982 - 85_10': 10, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmax_2': 2, 'all_rows_11': 11, 'years for jazz_12': 12, '3_13': 13, 'player_14': 14, 'john drew_15': 15}

{'and_5': 'and', 'result_6': 'true', 'eq_1': 'eq', 'nth_max_0': 'nth_max', 'all_rows_7': 'all_rows', 'years for jazz_8': 'years for jazz', '3_9': '3', '1982 - 85_10': '1982 - 85', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmax_2': 'nth_argmax', 'all_rows_11': 'all_rows', 'years for jazz_12': 'years for jazz', '3_13': '3', 'player_14': 'player', 'john drew_15': 'john drew'}

{'and_5': [6], 'result_6': [], 'eq_1': [5], 'nth_max_0': [1], 'all_rows_7': [0], 'years for jazz_8': [0], '3_9': [0], '1982 - 85_10': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'nth_argmax_2': [3], 'all_rows_11': [2], 'years for jazz_12': [2], '3_13': [2], 'player_14': [3], 'john drew_15': [4]}

['player', 'no', 'nationality', 'position', 'years for jazz', 'school / club team']

[['adrian dantley', '4', 'united states', 'guard - forward', '1979 - 86', 'notre dame'], ['brad davis', '12', 'united states', 'guard', '1979 - 80', 'maryland'], ['darryl dawkins', '45', 'united states', 'center', '1987 - 88', 'maynard evans hs'], ['paul dawkins', '31', 'united states', 'guard', '1979 - 80', 'northern illinois'], ['greg deane', '33', 'united states', 'guard', '1979 - 80', 'utah'], ['james donaldson', '54', 'united states', 'center', '1993 - 95', 'washington state'], ['john drew', '22', 'united states', 'guard - forward', '1982 - 85', 'gardner - webb']]

1973 ohio state buckeyes football team

https://en.wikipedia.org/wiki/1973_Ohio_State_Buckeyes_football_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17824926-1.html.csv

comparative

the ohio state buckeyes team had a game against iowa earlier than michigan .

{'row_1': '9', 'row_2': '10', 'col': '1', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', 'iowa'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose opponent record fuzzily matches to iowa .', 'tostr': 'filter_eq { all_rows ; opponent ; iowa }'}, 'date'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; opponent ; iowa } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to iowa . take the date record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'opponent', '4 michigan'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose opponent record fuzzily matches to 4 michigan .', 'tostr': 'filter_eq { all_rows ; opponent ; 4 michigan }'}, 'date'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; opponent ; 4 michigan } ; date }', 'tointer': 'select the rows whose opponent record fuzzily matches to 4 michigan . take the date record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; opponent ; iowa } ; date } ; hop { filter_eq { all_rows ; opponent ; 4 michigan } ; date } } = true', 'tointer': 'select the rows whose opponent record fuzzily matches to iowa . take the date record of this row . select the rows whose opponent record fuzzily matches to 4 michigan . take the date record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; opponent ; iowa } ; date } ; hop { filter_eq { all_rows ; opponent ; 4 michigan } ; date } } = true

select the rows whose opponent record fuzzily matches to iowa . take the date record of this row . select the rows whose opponent record fuzzily matches to 4 michigan . 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, 'opponent_7': 7, 'iowa_8': 8, 'date_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, '4 michigan_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', 'opponent_7': 'opponent', 'iowa_8': 'iowa', 'date_9': 'date', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', '4 michigan_12': '4 michigan', 'date_13': 'date'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'iowa_8': [0], 'date_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], '4 michigan_12': [1], 'date_13': [3]}

['date', 'opponent', 'rank', 'site', 'result', 'attendance']

[['september 15', 'minnesota', '3', 'ohio stadium columbus , oh', 'w56 - 7', '86005'], ['september 29', 'tcu', '3', 'ohio stadium columbus , oh', 'w37 - 3', '87439'], ['october 6', 'washington state', '1', 'ohio stadium columbus , oh', 'w27 - 3', '87425'], ['october 13', 'wisconsin', '1', 'camp randall stadium madison , wi', 'w24 - 0', '77413'], ['october 20', 'indiana', '1', 'memorial stadium bloomington , in', 'w37 - 7', '53183'], ['october 27', 'northwestern', '1', 'ohio stadium columbus , oh', 'w60 - 0', '87453'], ['november 3', 'illinois', '1', 'memorial stadium champaign , il', 'w30 - 0', '60707'], ['november 10', 'michigan state', '1', 'ohio stadium columbus , oh', 'w35 - 0', '87600'], ['november 17', 'iowa', '1', 'ohio stadium columbus , oh', 'w55 - 13', '87447'], ['november 24', '4 michigan', '1', 'michigan stadium ann arbor , mi', 't 10 - 10', '105223'], ['january 1', '7 usc', '4', 'rose bowl pasadena , ca ( rose bowl )', 'w42 - 21', '105267']]

united states house of representatives elections , 1800

https://en.wikipedia.org/wiki/United_States_House_of_Representatives_elections%2C_1800

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-2668401-12.html.csv

majority

the majority of the representatives elected from pennsylvania were from the democratic - republican party .

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

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

most_eq { all_rows ; party ; democratic - republican } = true

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

1

1

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

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

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

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

[['pennsylvania 1', 'robert waln', 'federalist', '1798 ( special )', 'retired democratic - republican gain', 'william jones ( dr ) 50.2 % francis gurney ( f ) 49.8 %'], ['pennsylvania 2', 'michael leib', 'democratic - republican', '1798', 're - elected', 'michael leib ( dr ) 77.8 % john lardner ( f ) 22.2 %'], ['pennsylvania 5', 'joseph hiester', 'democratic - republican', '1797 ( special )', 're - elected', 'joseph hiester ( dr ) 83.2 % roswell wells ( f ) 16.8 %'], ['pennsylvania 6', 'john a hanna', 'democratic - republican', '1796', 're - elected', 'john a hanna ( dr ) 74.6 % samuel maclay ( f ) 25.4 %'], ['pennsylvania 7', 'john w kittera', 'federalist', '1791', 'retired federalist hold', 'thomas boude ( f ) 54.1 % john whitehill ( dr ) 45.9 %'], ['pennsylvania 8', 'thomas hartley', 'federalist', '1788', 'retired democratic - republican gain', 'john stewart ( dr ) 54.8 % john eddie ( f ) 45.2 %'], ['pennsylvania 9', 'andrew gregg', 'democratic - republican', '1791', 're - elected', 'andrew gregg ( dr ) 72.6 % david mitchell ( f ) 27.4 %'], ['pennsylvania 10', 'henry woods', 'federalist', '1798', 're - elected', 'henry woods ( f ) 53.6 % david bard ( dr ) 46.4 %']]

2005 - 06 u.s. città di palermo season

https://en.wikipedia.org/wiki/2005%E2%80%9306_U.S._Citt%C3%A0_di_Palermo_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11361788-3.html.csv

ordinal

the 1st round - 1st leg of the 2005 - 06 u.s. città di palermo season had the 4th highest attendance .

{'row': '1', 'col': '6', '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', 'attendance', '4'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; attendance ; 4 }'}, 'round'], 'result': '1st round - 1st leg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 4 } ; round }'}, '1st round - 1st leg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; round } ; 1st round - 1st leg } = true', 'tointer': 'select the row whose attendance record of all rows is 4th maximum . the round record of this row is 1st round - 1st leg .'}

eq { hop { nth_argmax { all_rows ; attendance ; 4 } ; round } ; 1st round - 1st leg } = true

select the row whose attendance record of all rows is 4th maximum . the round record of this row is 1st round - 1st leg .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '4_6': 6, 'round_7': 7, '1st round - 1st leg_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', '4_6': '4', 'round_7': 'round', '1st round - 1st leg_8': '1st round - 1st leg'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '4_6': [0], 'round_7': [1], '1st round - 1st leg_8': [2]}

['date and time', 'round', 'opponent', 'venue', 'result', 'attendance']

[['september 15 , 2005 - 20.30', '1st round - 1st leg', 'anorthosis famagusta', 'home', 'won 2 - 1', '13047'], ['september 29 , 2005 - 17.00', '1st round - 2nd leg', 'anorthosis famagusta', 'away', 'won 4 - 0', '12000'], ['october 20 , 2005 - 17.00', 'group stage - group b', 'maccabi petah tikva', 'away', 'won 2 - 1', '2000'], ['november 3 , 2005 - 21.00', 'group stage - group b', 'lokomotiv moscow', 'home', 'drew 0 - 0', '15823'], ['november 24 , 2005 - 21.15', 'group stage - group b', 'espanyol', 'away', 'drew 1 - 1', '22000'], ['december 15 , 2005 - 20.45', 'group stage - group b', 'brøndby', 'home', 'won 3 - 0', '4521'], ['february 16 , 2006 - 20.45', 'round of 32 - 1st leg', 'slavia praha', 'away', 'lost 1 - 2', '6706'], ['february 23 , 2006 - 16.00', 'round of 32 - 2nd leg', 'slavia praha', 'home', 'won 1 - 0', '8063'], ['march 9 , 2006 - 18.00', 'round of 16 - 1st leg', 'schalke 04', 'home', 'won 1 - 0', '10581'], ['march 16 , 2006 - 20.30', 'round of 16 - 2nd leg', 'schalke 04', 'away', 'lost 0 - 3', '52151']]

1989 toronto blue jays season

https://en.wikipedia.org/wiki/1989_Toronto_Blue_Jays_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12207158-9.html.csv

aggregation

the 1989 toronto blue jays season had an average of about 49,849.4 attendees per game .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '49849.4', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '49849.4', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '49849.4'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 49849.4 } = true', 'tointer': 'the average of the attendance record of all rows is 49849.4 .'}

round_eq { avg { all_rows ; attendance } ; 49849.4 } = true

the average of the attendance record of all rows is 49849.4 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '49849.4_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '49849.4_5': '49849.4'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '49849.4_5': [1]}

['date', 'opponent', 'score', 'loss', 'attendance', 'series']

[['october 3', 'athletics', '7 - 3', 'stieb ( 0 - 1 )', '49435', '0 - 1'], ['october 4', 'athletics', '6 - 3', 'stottlemyre ( 0 - 1 )', '49444', '0 - 2'], ['october 6', 'athletics', '7 - 3', 'davis ( 0 - 1 )', '50268', '1 - 2'], ['october 7', 'athletics', '6 - 5', 'flanagan ( 0 - 1 )', '50076', '1 - 3'], ['october 8', 'athletics', '4 - 3', 'stieb ( 0 - 2 )', '50024', '1 - 4']]

2009 atp world tour masters 1000

https://en.wikipedia.org/wiki/2009_ATP_World_Tour_Masters_1000

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17057363-1.html.csv

superlative

cincinnati masters is the first atp world tour masters 1000 tournament that took place in the united states .

{'scope': 'subset', 'col_superlative': '5', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1,2', 'subset': {'col': '2', 'criterion': 'equal', 'value': 'united states'}}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmin', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'country', 'united states'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; country ; united states }', 'tointer': 'select the rows whose country record fuzzily matches to united states .'}, 'began'], 'result': None, 'ind': 1, 'tostr': 'argmin { filter_eq { all_rows ; country ; united states } ; began }'}, 'tournament'], 'result': 'cincinnati masters', 'ind': 2, 'tostr': 'hop { argmin { filter_eq { all_rows ; country ; united states } ; began } ; tournament }'}, 'cincinnati masters'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { argmin { filter_eq { all_rows ; country ; united states } ; began } ; tournament } ; cincinnati masters } = true', 'tointer': 'select the rows whose country record fuzzily matches to united states . select the row whose began record of these rows is minimum . the tournament record of this row is cincinnati masters .'}

eq { hop { argmin { filter_eq { all_rows ; country ; united states } ; began } ; tournament } ; cincinnati masters } = true

select the rows whose country record fuzzily matches to united states . select the row whose began record of these rows is minimum . the tournament record of this row is cincinnati masters .

4

4

{'str_eq_3': 3, 'result_4': 4, 'str_hop_2': 2, 'argmin_1': 1, 'filter_str_eq_0': 0, 'all_rows_5': 5, 'country_6': 6, 'united states_7': 7, 'began_8': 8, 'tournament_9': 9, 'cincinnati masters_10': 10}

{'str_eq_3': 'str_eq', 'result_4': 'true', 'str_hop_2': 'str_hop', 'argmin_1': 'argmin', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_5': 'all_rows', 'country_6': 'country', 'united states_7': 'united states', 'began_8': 'began', 'tournament_9': 'tournament', 'cincinnati masters_10': 'cincinnati masters'}

{'str_eq_3': [4], 'result_4': [], 'str_hop_2': [3], 'argmin_1': [2], 'filter_str_eq_0': [1], 'all_rows_5': [0], 'country_6': [0], 'united states_7': [0], 'began_8': [1], 'tournament_9': [2], 'cincinnati masters_10': [3]}

['tournament', 'country', 'location', 'current venue', 'began', 'court surface']

[['indian wells masters', 'united states', 'indian wells', 'indian wells tennis garden', '1987', 'hard'], ['miami masters', 'united states', 'miami', 'tennis center at crandon park', '1987', 'hard'], ['monte carlo masters', 'monaco', 'roquebrune - cap - martin , france', 'monte carlo country club', '1897', 'clay'], ['rome masters', 'italy', 'rome', 'foro italico', '1930', 'clay'], ['madrid masters', 'spain', 'madrid', 'park manzanares', '2002', 'clay'], ['canada masters', 'canada', 'montreal / toronto', 'stade uniprix / rexall centre', '1881', 'hard'], ['cincinnati masters', 'united states', 'mason , ohio', 'lindner family tennis center', '1899', 'hard'], ['shanghai masters', 'china', 'shanghai', 'qi zhong stadium', '2009', 'hard'], ['paris masters', 'france', 'paris', 'palais omnisports de paris - bercy', '1968', 'hard ( i )']]

portuguese legislative election , 2005

https://en.wikipedia.org/wiki/Portuguese_legislative_election%2C_2005

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-1463383-1.html.csv

majority

the majority of polls in 2005 showed at least 42 % support for the socialist party .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '42 %', 'subset': None}

{'func': 'most_greater_eq', 'args': ['all_rows', 'socialist', '42 %'], 'result': True, 'ind': 0, 'tointer': 'for the socialist records of all rows , most of them are greater than or equal to 42 % .', 'tostr': 'most_greater_eq { all_rows ; socialist ; 42 % } = true'}

most_greater_eq { all_rows ; socialist ; 42 % } = true

for the socialist records of all rows , most of them are greater than or equal to 42 % .

1

1

{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'socialist_3': 3, '42%_4': 4}

{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'socialist_3': 'socialist', '42%_4': '42 %'}

{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'socialist_3': [0], '42%_4': [0]}

['date released', 'polling institute', 'socialist', 'social democratic', 'peoples party', 'green - communist', 'left bloc', 'lead']

[['february 20 , 2005', 'election results', '45.0 % 121 seats', '28.8 % 75 seats', '7.2 % 12 seats', '7.5 % 14 seats', '6.4 % 8 seats', '16.2 %'], ['february 18 , 2005', 'aximage', '46.8 %', '29.6 %', '7.3 %', '7.0 %', '5.5 %', '17.2 %'], ['february 18 , 2005', 'marktest', '46.0 %', '26.8 %', '7.5 %', '8.9 %', '7.7 %', '19.2 %'], ['february 18 , 2005', 'eurosondagem', '45.0 %', '30.6 %', '7.7 %', '7.7 %', '5.7 %', '14.4 %'], ['february 18 , 2005', 'ipom', '46.0 %', '30.0 %', '8.0 %', '6.0 %', '7.0 %', '16.0 %'], ['february 18 , 2005', 'intercampus', '45.9 %', '30.3 %', '7.1 %', '7.6 %', '5.2 %', '15.6 %'], ['february 17 , 2005', 'tns / euroteste', '39.0 %', '28.0 %', '7.0 %', '6.0 %', '6.0 %', '11.0 %'], ['february 17 , 2005', 'universidade católica', '46.0 %', '31.0 %', '6.0 %', '7.0 %', '7.0 %', '15.0 %'], ['february 12 , 2005', 'eurosondagem', '44.4 %', '31.3 %', '7.4 %', '6.9 %', '6.4 %', '13.1 %'], ['february 11 , 2005', 'aximage', '44.7 %', '27.4 %', '6.4 %', '7.1 %', '4.8 %', '17.3 %'], ['february 4 , 2005', 'ipom', '49.0 %', '31.0 %', '8.0 %', '6.0 %', '5.0 %', '18.0 %'], ['february 4 , 2005', 'aximage', '43.5 %', '29.3 %', '7.0 %', '5.6 %', '3.5 %', '14.2 %'], ['february 3 , 2005', 'intercampus', '46.5 %', '31.6 %', '4.8 %', '8.1 %', '4.5 %', '14.9 %'], ['january 29 , 2005', 'eurosondagem', '46.1 %', '32.1 %', '7.0 %', '6.6 %', '4.6 %', '14.0 %'], ['january 28 , 2005', 'marktest', '45.1 %', '27.7 %', '6.3 %', '7.7 %', '8.1 %', '17.5 %'], ['january 28 , 2005', 'aximage', '43.3 %', '27.4 %', '6.3 %', '5.8 %', '5.0 %', '15.9 %'], ['january 28 , 2005', 'universidade católica', '46.0 %', '28.0 %', '6.0 %', '8.0 %', '8.0 %', '18.0 %'], ['january 27 , 2005', 'tns / euroteste', '40.0 %', '32.0 %', '6.0 %', '4.0 %', '5.0 %', '8.0 %'], ['january 21 , 2005', 'axiamge', '42.8 %', '28.7 %', '7.1 %', '6.2 %', '4.3 %', '14.1 %']]

mack hellings

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1252130-1.html.csv

aggregation

mack hellings drove a total number of 522 laps in his career .

{'scope': 'all', 'col': '6', 'type': 'sum', 'result': '522', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'laps'], 'result': '522', 'ind': 0, 'tostr': 'sum { all_rows ; laps }'}, '522'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; laps } ; 522 } = true', 'tointer': 'the sum of the laps record of all rows is 522 .'}

round_eq { sum { all_rows ; laps } ; 522 } = true

the sum of the laps record of all rows is 522 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'laps_4': 4, '522_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'laps_4': 'laps', '522_5': '522'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'laps_4': [0], '522_5': [1]}

['year', 'start', 'qual', 'rank', 'finish', 'laps']

[['1948', '21', '127.968', '6', '5', '200'], ['1949', '14', '128.260', '11', '16', '172'], ['1950', '26', '130.687', '20', '13', '132'], ['1951', '23', '132.925', '22', '31', '18']]

the sunday night project

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1590967-2.html.csv

majority

all of the episodes aired in the year 2006 .

{'scope': 'all', 'col': '2', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '2006', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'air date', '2006'], 'result': True, 'ind': 0, 'tointer': 'for the air date records of all rows , all of them fuzzily match to 2006 .', 'tostr': 'all_eq { all_rows ; air date ; 2006 } = true'}

all_eq { all_rows ; air date ; 2006 } = true

for the air date records of all rows , all of them fuzzily match to 2006 .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'air date_3': 3, '2006_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'air date_3': 'air date', '2006_4': '2006'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'air date_3': [0], '2006_4': [0]}

['episode number', 'air date', 'guest host', 'musical guest ( song performed )', 'who knows the most about the guest host panelists']

[['1', '6 january 2006', 'billie piper', 'texas ( sleep )', 'jade goody and kenzie'], ['2', '13 january 2006', 'lorraine kelly', 'editors ( munich )', 'myleene klass and phil tufnell'], ['3', '20 january 2006', 'christian slater', "the kooks ( you do n't love me )", 'lady isabella hervey and fearne cotton'], ['4', '27 january 2006', 'denise van outen', 'boy kill boy ( back again )', 'bez and nadia almada'], ['5', '3 february 2006', 'michael barrymore', 'the ordinary boys ( boys will be boys )', 'nancy sorrell and samia smith'], ['6', '10 february 2006', 'jamie oliver', 'kubb ( grow )', 'tara palmer - tomkinson and chantelle houghton'], ['7', '17 february 2006', 'jessie wallace', 'hard - fi ( hard to beat )', 'caprice bourret and hilda braid'], ['8', '24 february 2006', 'trisha goddard', 'the automatic ( raoul )', 'faria alam and pete burns']]

acc - big ten challenge

https://en.wikipedia.org/wiki/ACC%E2%80%93Big_Ten_Challenge

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1672976-1.html.csv

count

four teams in the acc - big ten challenge have recorded zero away losses .

{'scope': 'all', 'criterion': 'equal', 'value': '0', 'result': '4', 'col': '7', 'subset': None}

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

eq { count { filter_eq { all_rows ; away losses ; 0 } } ; 4 } = true

select the rows whose away losses record is equal to 0 . the number of such rows is 4 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, 'away losses_5': 5, '0_6': 6, '4_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'away losses_5': 'away losses', '0_6': '0', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'away losses_5': [0], '0_6': [0], '4_7': [2]}

['institution', 'wins', 'loss', 'home wins', 'home losses', 'away wins', 'away losses', 'neutral wins', 'neutral losses']

[['boston college eagles', '6', '1', '3', '1', '3', '0', '0', '0'], ['clemson tigers', '9', '5', '4', '3', '5', '2', '0', '0'], ['duke blue devils', '12', '2', '5', '0', '3', '2', '4', '0'], ['florida state seminoles', '6', '8', '4', '3', '2', '5', '0', '0'], ['georgia tech yellow jackets', '4', '9', '3', '2', '1', '6', '0', '1'], ['maryland terrapins', '10', '4', '5', '1', '4', '1', '1', '2'], ['miami hurricanes', '2', '4', '2', '1', '0', '3', '0', '0'], ['north carolina tar heels', '7', '7', '3', '3', '2', '4', '2', '0'], ['nc state wolfpack', '5', '8', '4', '2', '1', '6', '0', '0'], ['notre dame fighting irish', '0', '0', '0', '0', '0', '0', '0', '0'], ['pitt panthers', '0', '0', '0', '0', '0', '0', '0', '0'], ['syracuse orange', '0', '0', '0', '0', '0', '0', '0', '0'], ['virginia cavaliers', '8', '5', '5', '1', '3', '4', '0', '0'], ['virginia tech hokies', '3', '5', '2', '2', '1', '3', '0', '0'], ['wake forest demon deacons', '10', '3', '6', '1', '4', '2', '0', '0'], ['overall', '82', '61', '46', '20', '29', '38', '7', '3']]

1959 portuguese grand prix

https://en.wikipedia.org/wiki/1959_Portuguese_Grand_Prix

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122212-1.html.csv

majority

the majority of drivers were at least 2 laps behind the leader at the end of the 1959 portuguese grand prix .

{'scope': 'all', 'col': '4', 'most_or_all': 'most', 'criterion': 'greater_than_eq', 'value': '2', 'subset': None}

{'func': 'most_greater_eq', 'args': ['all_rows', 'time / retired', '2'], 'result': True, 'ind': 0, 'tointer': 'for the time / retired records of all rows , most of them are greater than or equal to 2 .', 'tostr': 'most_greater_eq { all_rows ; time / retired ; 2 } = true'}

most_greater_eq { all_rows ; time / retired ; 2 } = true

for the time / retired records of all rows , most of them are greater than or equal to 2 .

1

1

{'most_greater_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'time / retired_3': 3, '2_4': 4}

{'most_greater_eq_0': 'most_greater_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'time / retired_3': 'time / retired', '2_4': '2'}

{'most_greater_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'time / retired_3': [0], '2_4': [0]}

['driver', 'constructor', 'laps', 'time / retired', 'grid']

[['stirling moss', 'cooper - climax', '62', '2:11:55.41', '1'], ['masten gregory', 'cooper - climax', '61', '+ 1 lap', '3'], ['dan gurney', 'ferrari', '61', '+ 1 lap', '6'], ['maurice trintignant', 'cooper - climax', '60', '+ 2 laps', '4'], ['harry schell', 'brm', '59', '+ 3 laps', '9'], ['roy salvadori', 'aston martin', '59', '+ 3 laps', '12'], ['ron flockhart', 'brm', '59', '+ 3 laps', '11'], ['carroll shelby', 'aston martin', '58', '+ 4 laps', '13'], ['tony brooks', 'ferrari', '57', '+ 5 laps', '10'], ['mário de araújo cabral', 'cooper - maserati', '56', '+ 6 laps', '14'], ['bruce mclaren', 'cooper - climax', '38', 'transmission', '8'], ['jack brabham', 'cooper - climax', '23', 'transmission', '2'], ['jo bonnier', 'brm', '10', 'engine', '5'], ['phil hill', 'ferrari', '5', 'accident', '7'], ['graham hill', 'lotus - climax', '5', 'accident', '15'], ['innes ireland', 'lotus - climax', '3', 'gearbox', '16']]

southern athletic conference of indiana

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18956862-1.html.csv

aggregation

on average , teams joined the southern athletic conference of indiana around 1977 .

{'scope': 'all', 'col': '7', 'type': 'average', 'result': '1977', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'year joined'], 'result': '1977', 'ind': 0, 'tostr': 'avg { all_rows ; year joined }'}, '1977'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; year joined } ; 1977 } = true', 'tointer': 'the average of the year joined record of all rows is 1977 .'}

round_eq { avg { all_rows ; year joined } ; 1977 } = true

the average of the year joined record of all rows is 1977 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'year joined_4': 4, '1977_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'year joined_4': 'year joined', '1977_5': '1977'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'year joined_4': [0], '1977_5': [1]}

['school', 'location', 'mascot', 'county', 'enrollment', 'ihsaa class', 'year joined', 'previous conference']

[['borden', 'borden', 'braves', '228', 'a', '10 clark', '1974', 'lost river'], ['crothersville', 'crothersville', 'tigers', '180', 'a', '36 jackson', '1974', 'mid - hoosier'], ['henryville', 'henryville', 'hornets', '347', 'aa', '10 clark', '1977', 'lost river'], ['lanesville', 'lanesville', 'eagles', '237', 'a', '31 harrison', '1979', 'blue river'], ['new washington', 'new washington', 'mustangs', '273', 'a', '10 clark', '1974', 'dixie - monon'], ['south central ( elizabeth )', 'elizabeth', 'rebels', '277', 'a', '31 harrison', '1979', 'blue river']]

2003 lexmark indy 300

https://en.wikipedia.org/wiki/2003_Lexmark_Indy_300

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15080993-2.html.csv

majority

most of the drivers during the 2003 lexmark indy 300 did 47 laps .

{'scope': 'all', 'col': '3', 'most_or_all': 'most', 'criterion': 'equal', 'value': '47', 'subset': None}

{'func': 'most_eq', 'args': ['all_rows', 'laps', '47'], 'result': True, 'ind': 0, 'tointer': 'for the laps records of all rows , most of them are equal to 47 .', 'tostr': 'most_eq { all_rows ; laps ; 47 } = true'}

most_eq { all_rows ; laps ; 47 } = true

for the laps records of all rows , most of them are equal to 47 .

1

1

{'most_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'laps_3': 3, '47_4': 4}

{'most_eq_0': 'most_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'laps_3': 'laps', '47_4': '47'}

{'most_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'laps_3': [0], '47_4': [0]}

['driver', 'team', 'laps', 'time / retired', 'grid', 'points']

[['ryan hunter - reay', 'american spirit team johansson', '47', '1:49:02.803', '12', '20'], ['darren manning', 'walker racing', '47', '+ 1.546 secs', '14', '16'], ['jimmy vasser', 'american spirit team johansson', '47', '+ 3.792 secs', '15', '14'], ['michel jourdain , jr', 'team rahal', '47', '+ 5.315 secs', '9', '12'], ['patrick carpentier', "team player 's", '47', '+ 5.837 secs', '11', '10'], ['gualter salles', 'dale coyne racing', '47', '+ 8.180 secs', '17', '8'], ['alex tagliani', 'rocketsports racing', '47', '+ 10.131 secs', '4', '6'], ['rodolfo lavín', 'walker racing', '47', '+ 11.673 secs', '18', '5'], ['geoff boss', 'dale coyne racing', '47', '+ 50.728 secs', '19', '4'], ['mario domínguez', 'herdez competition', '46', '+ 1 lap', '8', '3'], ['mika salo', 'pk racing', '46', '+ 1 lap', '10', '2'], ['adrian fernández', 'fernández racing', '46', '+ 1 lap', '5', '1'], ['paul tracy', "team player 's", '45', '+ 2 laps', '3', '0'], ['mario haberfeld', 'mi - jack conquest racing', '43', '+ 4 laps', '16', '0'], ['bruno junqueira', 'newman / haas racing', '36', 'contact', '2', '2'], ['roberto moreno', 'herdez competition', '23', 'contact', '7', '0'], ['sébastien bourdais', 'newman - haas racing', '11', 'contact', '1', '1'], ['tiago monteiro', 'fittipaldi - dingman racing', '3', 'mechanical', '13', '0'], ['oriol servià', 'patrick racing', '1', 'contact', '6', '0']]

1981 seattle seahawks season

https://en.wikipedia.org/wiki/1981_Seattle_Seahawks_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-13258972-2.html.csv

aggregation

the seattle seahawks scored an average of 21.8 points over the course of 7 home games during the 1981 season .

{'scope': 'subset', 'col': '4', 'type': 'average', 'result': '21.8', 'subset': {'col': '5', 'criterion': 'equal', 'value': 'kingdome'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game site', 'kingdome'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; game site ; kingdome }', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome .'}, 'result'], 'result': '21.8', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; game site ; kingdome } ; result }'}, '21.8'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; game site ; kingdome } ; result } ; 21.8 } = true', 'tointer': 'select the rows whose game site record fuzzily matches to kingdome . the average of the result record of these rows is 21.8 .'}

round_eq { avg { filter_eq { all_rows ; game site ; kingdome } ; result } ; 21.8 } = true

select the rows whose game site record fuzzily matches to kingdome . the average of the result record of these rows is 21.8 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'game site_5': 5, 'kingdome_6': 6, 'result_7': 7, '21.8_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'game site_5': 'game site', 'kingdome_6': 'kingdome', 'result_7': 'result', '21.8_8': '21.8'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'game site_5': [0], 'kingdome_6': [0], 'result_7': [1], '21.8_8': [2]}

['week', 'date', 'opponent', 'result', 'game site', 'record', 'attendance']

[['1', 'september 6 , 1981', 'cincinnati bengals', 'l 21 - 27', 'riverfront stadium', '0 - 1', '41177'], ['2', 'september 13 , 1981', 'denver broncos', 'w 13 - 10', 'kingdome', '1 - 1', '58513'], ['3', 'september 20 , 1981', 'oakland raiders', 'l 10 - 20', 'oakland - alameda county coliseum', '1 - 2', '45725'], ['4', 'september 27 , 1981', 'kansas city chiefs', 'l 14 - 20', 'kingdome', '1 - 3', '59255'], ['5', 'october 4 , 1981', 'san diego chargers', 'l 10 - 24', 'jack murphy stadium', '1 - 4', '51463'], ['6', 'october 11 , 1981', 'houston oilers', 'l 17 - 35', 'the astrodome', '1 - 5', '42671'], ['7', 'october 18 , 1981', 'new york giants', 'l 0 - 32', 'kingdome', '1 - 6', '56134'], ['8', 'october 25 , 1981', 'new york jets', 'w 19 - 13', 'shea stadium', '2 - 6', '49678'], ['9', 'november 1 , 1981', 'green bay packers', 'l 24 - 34', 'lambeau field', '2 - 7', '49467'], ['10', 'november 8 , 1981', 'pittsburgh steelers', 'w 24 - 21', 'kingdome', '3 - 7', '59058'], ['11', 'november 16 , 1981', 'san diego chargers', 'w 44 - 23', 'kingdome', '4 - 7', '58628'], ['12', 'november 22 , 1981', 'kansas city chiefs', 'l 13 - 40', 'arrowhead stadium', '4 - 8', '49002'], ['13', 'november 29 , 1981', 'oakland raiders', 'l 31 - 32', 'kingdome', '4 - 9', '57147'], ['14', 'december 6 , 1981', 'new york jets', 'w 27 - 23', 'kingdome', '5 - 9', '53105'], ['15', 'december 13 , 1981', 'denver broncos', 'l 13 - 23', 'mile high stadium', '5 - 10', '74527']]

orlando magic all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-15621965-2.html.csv

count

two of the players had previously played for kentucky .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'kentucky', 'result': '2', 'col': '6', 'subset': None}

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

eq { count { filter_eq { all_rows ; school / club team ; kentucky } } ; 2 } = true

select the rows whose school / club team record fuzzily matches to kentucky . 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, 'school / club team_5': 5, 'kentucky_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', 'school / club team_5': 'school / club team', 'kentucky_6': 'kentucky', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'school / club team_5': [0], 'kentucky_6': [0], '2_7': [2]}

['player', 'no', 'nationality', 'position', 'years in orlando', 'school / club team']

[['matt barnes', '22', 'united states', 'guard - forward', '2009 - 2010', 'ucla'], ['andre barrett', '11', 'united states', 'guard', '2005', 'seton hall'], ['brandon bass', '30', 'united states', 'forward', '2009 - 2011', 'louisiana state'], ['tony battie', '4', 'united states', 'forward - center', '2004 - 2009', 'texas tech'], ['david benoit', '2', 'united states', 'forward', '1998', 'alabama'], ['keith bogans', '3', 'united states', 'guard', '2003 - 2004', 'kentucky'], ['keith bogans', '10', 'united states', 'guard', '2006 - 2009', 'kentucky'], ['anthony bonner', '24', 'united states', 'forward', '1995 - 1996', 'st louis'], ['anthony bowie', '14', 'united states', 'guard', '1991 - 1996', 'oklahoma'], ['earl boykins', '11', 'united states', 'guard', '1999', 'eastern michigan'], ['michael bradley', '7', 'united states', 'forward', '2004 - 2005', 'villanova'], ['dee brown', '7', 'united states', 'guard', '2000 - 2002', 'jacksonville'], ['jud buechler', '30', 'united states', 'guard - forward', '2001 - 2002', 'arizona']]

list of tvb series ( 2007 )

https://en.wikipedia.org/wiki/List_of_TVB_series_%282007%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11173827-1.html.csv

majority

the majority of tvb series in 2007 drew over 2 million hk viewers .

{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '2', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'hk viewers', '2'], 'result': True, 'ind': 0, 'tointer': 'for the hk viewers records of all rows , most of them are greater than 2 .', 'tostr': 'most_greater { all_rows ; hk viewers ; 2 } = true'}

most_greater { all_rows ; hk viewers ; 2 } = true

for the hk viewers records of all rows , most of them are greater than 2 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'hk viewers_3': 3, '2_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'hk viewers_3': 'hk viewers', '2_4': '2'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'hk viewers_3': [0], '2_4': [0]}

['rank', 'english title', 'chinese title', 'average', 'peak', 'premiere', 'finale', 'hk viewers']

[['1', 'the family link', '師奶兵團', '33', '42', '31', '33', '2.12 million'], ['2', 'fathers and sons', '爸爸閉翳', '32', '40', '31', '37', '2.11 million'], ['3', 'heart of greed', '溏心風暴', '32', '48', '29', '40', '2.08 million'], ['4', 'ten brothers', '十兄弟', '32', '39', '29', '36', '2.05 million'], ['5', 'on the first beat', '學警出更', '31', '38', '30', '35', '2.03 million'], ['6', 'the green grass of home', '緣來自有機', '31', '36', '29', '33', '2.01 million'], ['7', 'dicey business', '賭場風雲', '31', '37', '30', '34', '1.99 million'], ['8', 'steps', '舞動全城', '31', '36', '31', '32', '1.98 million'], ['9', 'the drive of life', '歲月風雲', '30', '39', '31', '33', '1.97 million']]

flavio cipolla

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16474033-9.html.csv

count

flavio cipolla played a total of three tennis tournaments on a hard surface .

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

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

eq { count { filter_eq { all_rows ; surface ; hard } } ; 3 } = true

select the rows whose surface record fuzzily matches to hard . 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, 'surface_5': 5, 'hard_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', 'surface_5': 'surface', 'hard_6': 'hard', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'surface_5': [0], 'hard_6': [0], '3_7': [2]}

['date', 'tournament', 'surface', 'opponent', 'score']

[['29 august 2005', 'freudenstadt , germany', 'clay', 'sergio roitman', '7 - 5 , 6 - 4'], ['6 september 2005', 'genoa , italy', 'clay', 'potito starace', '6 - 3 , 7 - 6 ( 7 - 3 )'], ['3 april 2006', 'monza , italy', 'clay', 'nicolas devilder', '6 - 2 , 7 - 5'], ['28 july 2008', 'tampere , finland', 'clay', 'mathieu montcourt', '6 - 2 , 6 - 2'], ['9 january 2010', 'nouméa , new caledonia', 'hard', 'florian mayer', '6 - 3 , 6 - 0'], ['4 juny 2011', 'prostějov , czech republic', 'clay', 'yuri schukin', '6 - 4 , 4 - 6 , 6 - 0'], ['13 november 2011', 'loughborough , uk', 'hard', 'tobias kamke', '2 - 6 , 5 - 7'], ['9 september 2012', 'saint - rémy - de - provence , france', 'hard', 'josselin ouanna', '4 - 6 , 5 - 7']]

1988 los angeles rams season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11157007-1.html.csv

ordinal

in the 1988 los angeles rams season , the 3rd highest crowd was on november 27 , 1988 .

{'row': '13', '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': 'november 27 , 1988', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; attendance ; 3 } ; date }'}, 'november 27 , 1988'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; november 27 , 1988 } = true', 'tointer': 'select the row whose attendance record of all rows is 3rd maximum . the date record of this row is november 27 , 1988 .'}

eq { hop { nth_argmax { all_rows ; attendance ; 3 } ; date } ; november 27 , 1988 } = true

select the row whose attendance record of all rows is 3rd maximum . the date record of this row is november 27 , 1988 .

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, 'november 27 , 1988_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', 'november 27 , 1988_8': 'november 27 , 1988'}

{'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], 'november 27 , 1988_8': [2]}

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

[['1', 'september 4 , 1988', 'green bay packers', 'w 34 - 7', '53769'], ['2', 'september 11 , 1988', 'detroit lions', 'w 17 - 10', '46262'], ['3', 'september 18 , 1988', 'los angeles raiders', 'w 22 - 17', '84870'], ['4', 'september 25 , 1988', 'new york giants', 'w 45 - 31', '75617'], ['5', 'october 2 , 1988', 'phoenix cardinals', 'l 41 - 27', '49830'], ['6', 'october 9 , 1988', 'atlanta falcons', 'w 33 - 0', '30852'], ['7', 'october 16 , 1988', 'san francisco 49ers', 'l 24 - 21', '65450'], ['8', 'october 23 , 1988', 'seattle seahawks', 'w 31 - 10', '57033'], ['9', 'october 30 , 1988', 'new orleans saints', 'w 12 - 10', '68238'], ['10', 'november 6 , 1988', 'philadelphia eagles', 'l 30 - 24', '65624'], ['11', 'november 13 , 1988', 'new orleans saints', 'l 14 - 10', '63305'], ['12', 'november 20 , 1988', 'san diego chargers', 'l 38 - 24', '45462'], ['13', 'november 27 , 1988', 'denver broncos', 'l 35 - 24', '74141'], ['14', 'december 5 , 1988', 'chicago bears', 'w 23 - 3', '65579'], ['15', 'december 11 , 1988', 'atlanta falcons', 'w 22 - 7', '42828'], ['16', 'december 18 , 1988', 'san francisco 49ers', 'w 38 - 16', '62444']]

2003 lexmark indy 300

https://en.wikipedia.org/wiki/2003_Lexmark_Indy_300

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15080993-2.html.csv

unique

tiago monteiro id the only driver having mechanical issues during the 2003 lexmark indy 300 .

{'scope': 'all', 'row': '18', 'col': '4', 'col_other': '1', 'criterion': 'equal', 'value': 'mechanical', 'subset': None}

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

and { only { filter_eq { all_rows ; time / retired ; mechanical } } ; eq { hop { filter_eq { all_rows ; time / retired ; mechanical } ; driver } ; tiago monteiro } } = true

select the rows whose time / retired record fuzzily matches to mechanical . there is only one such row in the table . the driver record of this unqiue row is tiago monteiro .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'time / retired_7': 7, 'mechanical_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'driver_9': 9, 'tiago monteiro_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'time / retired_7': 'time / retired', 'mechanical_8': 'mechanical', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'driver_9': 'driver', 'tiago monteiro_10': 'tiago monteiro'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'time / retired_7': [0], 'mechanical_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'driver_9': [2], 'tiago monteiro_10': [3]}

['driver', 'team', 'laps', 'time / retired', 'grid', 'points']

[['ryan hunter - reay', 'american spirit team johansson', '47', '1:49:02.803', '12', '20'], ['darren manning', 'walker racing', '47', '+ 1.546 secs', '14', '16'], ['jimmy vasser', 'american spirit team johansson', '47', '+ 3.792 secs', '15', '14'], ['michel jourdain , jr', 'team rahal', '47', '+ 5.315 secs', '9', '12'], ['patrick carpentier', "team player 's", '47', '+ 5.837 secs', '11', '10'], ['gualter salles', 'dale coyne racing', '47', '+ 8.180 secs', '17', '8'], ['alex tagliani', 'rocketsports racing', '47', '+ 10.131 secs', '4', '6'], ['rodolfo lavín', 'walker racing', '47', '+ 11.673 secs', '18', '5'], ['geoff boss', 'dale coyne racing', '47', '+ 50.728 secs', '19', '4'], ['mario domínguez', 'herdez competition', '46', '+ 1 lap', '8', '3'], ['mika salo', 'pk racing', '46', '+ 1 lap', '10', '2'], ['adrian fernández', 'fernández racing', '46', '+ 1 lap', '5', '1'], ['paul tracy', "team player 's", '45', '+ 2 laps', '3', '0'], ['mario haberfeld', 'mi - jack conquest racing', '43', '+ 4 laps', '16', '0'], ['bruno junqueira', 'newman / haas racing', '36', 'contact', '2', '2'], ['roberto moreno', 'herdez competition', '23', 'contact', '7', '0'], ['sébastien bourdais', 'newman - haas racing', '11', 'contact', '1', '1'], ['tiago monteiro', 'fittipaldi - dingman racing', '3', 'mechanical', '13', '0'], ['oriol servià', 'patrick racing', '1', 'contact', '6', '0']]

list of kyle xy episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11075747-4.html.csv

comparative

guy norman bee directed an episode of kyle xy before james head did .

{'row_1': '6', 'row_2': '7', 'col': '2', 'col_other': '4', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'guy norman bee'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose directed by record fuzzily matches to guy norman bee .', 'tostr': 'filter_eq { all_rows ; directed by ; guy norman bee }'}, 'episode'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; directed by ; guy norman bee } ; episode }', 'tointer': 'select the rows whose directed by record fuzzily matches to guy norman bee . take the episode record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'directed by', 'james head'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose directed by record fuzzily matches to james head .', 'tostr': 'filter_eq { all_rows ; directed by ; james head }'}, 'episode'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; directed by ; james head } ; episode }', 'tointer': 'select the rows whose directed by record fuzzily matches to james head . take the episode record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; directed by ; guy norman bee } ; episode } ; hop { filter_eq { all_rows ; directed by ; james head } ; episode } } = true', 'tointer': 'select the rows whose directed by record fuzzily matches to guy norman bee . take the episode record of this row . select the rows whose directed by record fuzzily matches to james head . take the episode record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; directed by ; guy norman bee } ; episode } ; hop { filter_eq { all_rows ; directed by ; james head } ; episode } } = true

select the rows whose directed by record fuzzily matches to guy norman bee . take the episode record of this row . select the rows whose directed by record fuzzily matches to james head . take the episode 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, 'directed by_7': 7, 'guy norman bee_8': 8, 'episode_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'directed by_11': 11, 'james head_12': 12, 'episode_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', 'directed by_7': 'directed by', 'guy norman bee_8': 'guy norman bee', 'episode_9': 'episode', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'directed by_11': 'directed by', 'james head_12': 'james head', 'episode_13': 'episode'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'directed by_7': [0], 'guy norman bee_8': [0], 'episode_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'directed by_11': [1], 'james head_12': [1], 'episode_13': [3]}

['series', 'episode', 'title', 'directed by', 'written by', 'original air date']

[['34', '1', 'it happened one night', 'chris grismer', 'eric tuchman', 'january 12 , 2009'], ['35', '2', 'psychic friend', 'michael robison', 'julie plec', 'january 19 , 2009'], ['36', '3', 'electric kiss', 'chris grismer', 'gayle abrams', 'january 26 , 2009'], ['37', '4', 'in the company of men', 'guy norman bee', 'daniel arkin', 'february 2 , 2009'], ['38', '5', 'life support', 'michael robison', 'bryan m holdman', 'february 9 , 2009'], ['39', '6', 'welcome to latnok', 'guy norman bee', 'rp gaborno & chris hollier', 'february 16 , 2009'], ['40', '7', 'chemistry 101', 'james head', 'steven lilien & bryan wynbrandt', 'february 23 , 2009'], ['41', '8', 'tell - tale heart', 'peter deluise', 'gayle abrams & brian ridings', 'march 2 , 2009'], ['42', '9', "guess who 's coming to dinner", 'james head', 'daniel arkin & andrea conway', 'march 9 , 2009']]

1991 national league championship series

https://en.wikipedia.org/wiki/1991_National_League_Championship_Series

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1742998-1.html.csv

aggregation

the average attendance at the 1991 national league championship games was just under 52,800 .

{'scope': 'all', 'col': '5', 'type': 'average', 'result': '52800', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'attendance'], 'result': '52800', 'ind': 0, 'tostr': 'avg { all_rows ; attendance }'}, '52800'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; attendance } ; 52800 } = true', 'tointer': 'the average of the attendance record of all rows is 52800 .'}

round_eq { avg { all_rows ; attendance } ; 52800 } = true

the average of the attendance record of all rows is 52800 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'attendance_4': 4, '52800_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'attendance_4': 'attendance', '52800_5': '52800'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'attendance_4': [0], '52800_5': [1]}

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

[['1', 'october 9', 'three rivers stadium', '2:51', '57347'], ['2', 'october 10', 'three rivers stadium', '2:46', '57533'], ['3', 'october 12', 'atlanta - fulton county stadium', '3:21', '50905'], ['4', 'october 13', 'atlanta - fulton county stadium', '3:43', '51109'], ['5', 'october 14', 'atlanta - fulton county stadium', '2:51', '51109'], ['6', 'october 16', 'three rivers stadium', '3:09', '54508'], ['7', 'october 17', 'three rivers stadium', '3:04', '46932']]

tomasz sikora

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1269400-2.html.csv

ordinal

tomasz sikora 's second best finish in the individual event was in 2004 .

{'row': '10', 'col': '2', 'order': '2', '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', 'individual', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; individual ; 2 }'}, 'event'], 'result': '2004 oberhof', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; individual ; 2 } ; event }'}, '2004 oberhof'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; individual ; 2 } ; event } ; 2004 oberhof } = true', 'tointer': 'select the row whose individual record of all rows is 2nd minimum . the event record of this row is 2004 oberhof .'}

eq { hop { nth_argmin { all_rows ; individual ; 2 } ; event } ; 2004 oberhof } = true

select the row whose individual record of all rows is 2nd minimum . the event record of this row is 2004 oberhof .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'individual_5': 5, '2_6': 6, 'event_7': 7, '2004 oberhof_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', 'individual_5': 'individual', '2_6': '2', 'event_7': 'event', '2004 oberhof_8': '2004 oberhof'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'individual_5': [0], '2_6': [0], 'event_7': [1], '2004 oberhof_8': [2]}

['event', 'individual', 'sprint', 'pursuit', 'mass start', 'relay']

[['1995 antholz', '1st', '29th', '-', '-', '7th'], ['1996 ruhpolding', '6th', '15th', '-', '-', '7th'], ['1997 brezno - osrblie', '28th', '17th', '21st', '-', '6th'], ['1998 pokljuka', '-', '-', '14th', '-', '-'], ['1999 kontiolahti', '14th', '59th', '-', '-', '14th'], ['2000 oslo', '32nd', '21st', '47th', '18th', '11th'], ['2001 pokljuka', '18th', '15th', '16th', '20th', '6th'], ['2002 oslo', '-', '-', '-', '25th', '-'], ['2003 khanty - mansiysk', '9th', '11th', '7th', '14th', '-'], ['2004 oberhof', '2nd', '11th', '7th', '14th', '-'], ['2005 hochfilzen', '-', '9th', '10th', '5th', '10th'], ['2005 khanty - mansiysk', '-', '-', '-', '-', '-'], ['2006 pokljuka', '-', '-', '-', '-', '-'], ['2007 antholz', '21st', '5th', '7th', '21st', '13th'], ['2008 östersund', '30th', '11th', '11th', '19th', '-'], ['2009 pyeongchang', '9th', '16th', '4th', '6th', '13th'], ['2010 khanty - mansiysk', '-', '-', '-', '-', '-']]

1940 vfl season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807253-8.html.csv

aggregation

the vfl crowd size on 15 june 1940 averaged 12,600 across five venues .

{'scope': 'subset', 'col': '6', 'type': 'average', 'result': '12,600', 'subset': {'col': '7', 'criterion': 'equal', 'value': '15 june 1940'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', '15 june 1940'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; date ; 15 june 1940 }', 'tointer': 'select the rows whose date record fuzzily matches to 15 june 1940 .'}, 'crowd'], 'result': '12,600', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; date ; 15 june 1940 } ; crowd }'}, '12,600'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; date ; 15 june 1940 } ; crowd } ; 12,600 } = true', 'tointer': 'select the rows whose date record fuzzily matches to 15 june 1940 . the average of the crowd record of these rows is 12,600 .'}

round_eq { avg { filter_eq { all_rows ; date ; 15 june 1940 } ; crowd } ; 12,600 } = true

select the rows whose date record fuzzily matches to 15 june 1940 . the average of the crowd record of these rows is 12,600 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, '15 june 1940_6': 6, 'crowd_7': 7, '12,600_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', '15 june 1940_6': '15 june 1940', 'crowd_7': 'crowd', '12,600_8': '12,600'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], '15 june 1940_6': [0], 'crowd_7': [1], '12,600_8': [2]}

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

[['collingwood', '6.13 ( 49 )', 'richmond', '10.15 ( 75 )', 'victoria park', '20000', '15 june 1940'], ['south melbourne', '12.9 ( 81 )', 'st kilda', '10.16 ( 76 )', 'lake oval', '12000', '15 june 1940'], ['north melbourne', '8.15 ( 63 )', 'geelong', '13.20 ( 98 )', 'arden street oval', '5000', '15 june 1940'], ['hawthorn', '8.17 ( 65 )', 'footscray', '15.20 ( 110 )', 'glenferrie oval', '10000', '15 june 1940'], ['essendon', '12.14 ( 86 )', 'carlton', '8.15 ( 63 )', 'windy hill', '16000', '15 june 1940'], ['melbourne', '12.15 ( 87 )', 'fitzroy', '12.13 ( 85 )', 'mcg', '19737', '17 june 1940']]

list of the busiest airports in the united states

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-18047346-5.html.csv

ordinal

the second highest number of people go through the airport that is located in alaska .

{'row': '2', 'col': '5', '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', 'tonnes', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; tonnes ; 2 }'}, 'location'], 'result': 'anchorage , alaska', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; tonnes ; 2 } ; location }'}, 'anchorage , alaska'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; tonnes ; 2 } ; location } ; anchorage , alaska } = true', 'tointer': 'select the row whose tonnes record of all rows is 2nd maximum . the location record of this row is anchorage , alaska .'}

eq { hop { nth_argmax { all_rows ; tonnes ; 2 } ; location } ; anchorage , alaska } = true

select the row whose tonnes record of all rows is 2nd maximum . the location record of this row is anchorage , alaska .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'tonnes_5': 5, '2_6': 6, 'location_7': 7, 'anchorage , alaska_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', 'tonnes_5': 'tonnes', '2_6': '2', 'location_7': 'location', 'anchorage , alaska_8': 'anchorage , alaska'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'tonnes_5': [0], '2_6': [0], 'location_7': [1], 'anchorage , alaska_8': [2]}

['rank', 'airport name', 'location', 'iata code', 'tonnes', '% chg 2010 / 11']

[['1', 'memphis international airport', 'memphis , tennessee', 'mem', '3916410', '0 0.0 %'], ['2', 'ted stevens anchorage international airport', 'anchorage , alaska', 'anc', '2543105', '0 3.9 %'], ['3', 'louisville international airport', 'louisville , kentucky', 'sdf', '2188422', '0 1.0 %'], ['4', 'miami international airport', 'miami , florida', 'mia', '1841929', '0 0.3 %'], ['5', 'los angeles international airport', 'los angeles , california', 'lax', '1681611', '0 3.8 %'], ['6', 'john f kennedy international airport', 'queens , new york', 'jfk', '1348992', '0 0.5 %'], ['7', "o'hare international airport", 'chicago , illinois', 'ord', '1311622', '0 4.7 %'], ['8', 'indianapolis international airport', 'indianapolis', 'ind', '0 971664', '0 4.0 %'], ['9', 'newark liberty international airport', 'newark , new jersey', 'ewr', '0 813209', '0 5.0 %']]

1975 dallas cowboys season

https://en.wikipedia.org/wiki/1975_Dallas_Cowboys_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16767061-2.html.csv

comparative

more people attended the game on november 10 , 1975 than attended on december 7 , 1975 .

{'row_1': '8', 'row_2': '12', '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', 'date', 'november 10 , 1975'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to november 10 , 1975 .', 'tostr': 'filter_eq { all_rows ; date ; november 10 , 1975 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; date ; november 10 , 1975 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to november 10 , 1975 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'december 7 , 1975'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose date record fuzzily matches to december 7 , 1975 .', 'tostr': 'filter_eq { all_rows ; date ; december 7 , 1975 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; date ; december 7 , 1975 } ; attendance }', 'tointer': 'select the rows whose date record fuzzily matches to december 7 , 1975 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; date ; november 10 , 1975 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 7 , 1975 } ; attendance } } = true', 'tointer': 'select the rows whose date record fuzzily matches to november 10 , 1975 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 7 , 1975 . take the attendance record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; date ; november 10 , 1975 } ; attendance } ; hop { filter_eq { all_rows ; date ; december 7 , 1975 } ; attendance } } = true

select the rows whose date record fuzzily matches to november 10 , 1975 . take the attendance record of this row . select the rows whose date record fuzzily matches to december 7 , 1975 . take the attendance 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, 'date_7': 7, 'november 10 , 1975_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'date_11': 11, 'december 7 , 1975_12': 12, 'attendance_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', 'date_7': 'date', 'november 10 , 1975_8': 'november 10 , 1975', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'date_11': 'date', 'december 7 , 1975_12': 'december 7 , 1975', 'attendance_13': 'attendance'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'date_7': [0], 'november 10 , 1975_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'date_11': [1], 'december 7 , 1975_12': [1], 'attendance_13': [3]}

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

[['1', 'september 21 , 1975', 'los angeles rams', 'w 18 - 7', '49091'], ['2', 'september 28 , 1975', 'st louis cardinals', 'w 37 - 31', '52417'], ['3', 'october 6 , 1975', 'detroit lions', 'w 36 - 10', '79384'], ['4', 'october 12 , 1975', 'new york giants', 'w 13 - 7', '56511'], ['5', 'october 19 , 1975', 'green bay packers', 'l 19 - 17', '64189'], ['6', 'october 26 , 1975', 'philadelphia eagles', 'w 20 - 17', '64889'], ['7', 'november 2 , 1975', 'washington redskins', 'l 30 - 24', '55004'], ['8', 'november 10 , 1975', 'kansas city chiefs', 'l 34 - 31', '63539'], ['9', 'november 16 , 1975', 'new england patriots', 'w 34 - 31', '60905'], ['10', 'november 23 , 1975', 'philadelphia eagles', 'w 27 - 17', '57893'], ['11', 'november 30 , 1975', 'new york giants', 'w 14 - 3', '53329'], ['12', 'december 7 , 1975', 'st louis cardinals', 'l 31 - 17', '49701'], ['13', 'december 13 , 1975', 'washington redskins', 'w 31 - 10', '61091'], ['14', 'december 21 , 1975', 'new york jets', 'w 31 - 21', '37279']]

1973 uefa cup final

https://en.wikipedia.org/wiki/1973_UEFA_Cup_Final

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15755354-2.html.csv

unique

fc koln was the only opposition team that did not score any goals .

{'scope': 'all', 'row': '3', 'col': '5', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': '0', 'subset': None}

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

and { only { filter_eq { all_rows ; aggregate score ; 0 } } ; eq { hop { filter_eq { all_rows ; aggregate score ; 0 } ; opposition } ; fc köln } } = true

select the rows whose aggregate score record fuzzily matches to 0 . there is only one such row in the table . the opposition record of this unqiue row is fc köln .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'aggregate score_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'opposition_9': 9, 'fc köln_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'aggregate score_7': 'aggregate score', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'opposition_9': 'opposition', 'fc köln_10': 'fc köln'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'aggregate score_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'opposition_9': [2], 'fc köln_10': [3]}

['round', 'opposition', 'first leg', 'second leg', 'aggregate score']

[['1st', 'aberdeen', '3 - 2 ( a )', '6 - 3 ( h )', '9 - 5'], ['2nd', 'hvidovre', '3 - 0 ( h )', '3 - 1 ( a )', '6 - 1'], ['3rd', 'fc köln', '0 - 0 ( a )', '5 - 0 ( h )', '5 - 0'], ['quarter - final', 'kaiserslautern', '2 - 1 ( a )', '7 - 1 ( h )', '9 - 2'], ['semi - final', 'twente', '3 - 0 ( h )', '2 - 1 ( a )', '5 - 1']]

face up ( album )

https://en.wikipedia.org/wiki/Face_Up_%28album%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15845800-3.html.csv

count

three of the cd releases occurred during june of 2001 .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'june 2001', 'result': '3', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'june 2001'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to june 2001 .', 'tostr': 'filter_eq { all_rows ; date ; june 2001 }'}], 'result': '3', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; june 2001 } }', 'tointer': 'select the rows whose date record fuzzily matches to june 2001 . the number of such rows is 3 .'}, '3'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; june 2001 } } ; 3 } = true', 'tointer': 'select the rows whose date record fuzzily matches to june 2001 . the number of such rows is 3 .'}

eq { count { filter_eq { all_rows ; date ; june 2001 } } ; 3 } = true

select the rows whose date record fuzzily matches to june 2001 . 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, 'date_5': 5, 'june 2001_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', 'date_5': 'date', 'june 2001_6': 'june 2001', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'june 2001_6': [0], '3_7': [2]}

['region', 'date', 'label', 'format', 'catalog']

[['japan', '20 june 2001', 'arista', 'cd', 'bvca - 21087'], ['europe', '25 june 2001', 'arista', 'cd', '74321 86632 2'], ['united kingdom', '25 june 2001', 'arista', 'cd', '74321 86346 2'], ['united kingdom', '2 june 2003', 'arista', 'remastered cd', '82876 54377 2'], ['europe', '2 august 2004', 'arista', 'remastered cd', '82876 54377 2']]

miracle ( celine dion album )

https://en.wikipedia.org/wiki/Miracle_%28Celine_Dion_album%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1097545-4.html.csv

count

the album was released eight times in october of 2004 .

{'scope': 'all', 'criterion': 'fuzzily_match', 'value': 'october', 'result': '8', 'col': '2', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'date', 'october'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose date record fuzzily matches to october .', 'tostr': 'filter_eq { all_rows ; date ; october }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; date ; october } }', 'tointer': 'select the rows whose date record fuzzily matches to october . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; date ; october } } ; 8 } = true', 'tointer': 'select the rows whose date record fuzzily matches to october . the number of such rows is 8 .'}

eq { count { filter_eq { all_rows ; date ; october } } ; 8 } = true

select the rows whose date record fuzzily matches to october . the number of such rows is 8 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'date_5': 5, 'october_6': 6, '8_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'date_5': 'date', 'october_6': 'october', '8_7': '8'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'date_5': [0], 'october_6': [0], '8_7': [2]}

['region', 'date', 'label', 'format', 'catalog']

[['europe', 'october 11 , 2004', 'sony bmg , columbia', 'cd', 'col 518748 9'], ['europe', 'october 11 , 2004', 'sony bmg , columbia', 'cd / dvd', 'col 518748 7'], ['united states', 'october 12 , 2004', 'epic', 'cd', '5187482'], ['united states', 'october 12 , 2004', 'epic', 'cd / dvd', '5187487'], ['canada', 'october 12 , 2004', 'sony bmg , columbia', 'cd', '5187482'], ['canada', 'october 12 , 2004', 'sony bmg , columbia', 'cd / dvd', '5187487'], ['australia', 'october 15 , 2004', 'sony bmg , epic', 'cd', '5187482'], ['australia', 'october 15 , 2004', 'sony bmg , epic', 'cd / dvd', '5187487'], ['south korea', 'november 16 , 2004', 'sony bmg , columbia', 'cd', 'cpk - 3337'], ['japan', 'december 22 , 2004', 'sony music japan , epic', 'cd', '5187482']]

2008 - 09 west ham united f.c. season

https://en.wikipedia.org/wiki/2008%E2%80%9309_West_Ham_United_F.C._season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18539546-8.html.csv

superlative

ferdinand was the player in the 2008 - 09 west ham united f.c. season that received the highest transfer fee .

{'scope': 'all', 'col_superlative': '5', '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', 'transfer fee'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; transfer fee }'}, 'name'], 'result': 'ferdinand', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; transfer fee } ; name }'}, 'ferdinand'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; transfer fee } ; name } ; ferdinand } = true', 'tointer': 'select the row whose transfer fee record of all rows is maximum . the name record of this row is ferdinand .'}

eq { hop { argmax { all_rows ; transfer fee } ; name } ; ferdinand } = true

select the row whose transfer fee record of all rows is maximum . the name record of this row is ferdinand .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'transfer fee_5': 5, 'name_6': 6, 'ferdinand_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'transfer fee_5': 'transfer fee', 'name_6': 'name', 'ferdinand_7': 'ferdinand'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'transfer fee_5': [0], 'name_6': [1], 'ferdinand_7': [2]}

['name', 'country', 'status', 'moving to', 'transfer fee']

[['solano', 'per', 'transferred', 'released', 'free'], ['zamora', 'eng', 'transferred', 'fulham', '4.8 m'], ['paintsil', 'gha', 'transferred', 'fulham', '1.5 m'], ['wright', 'eng', 'transferred', 'ipswich town', '0.5 m'], ['ljungberg', 'swe', 'transferred', 'released', 'free'], ['ferdinand', 'eng', 'transferred', 'sunderland', '8 m'], ['mccartney', 'nir', 'transferred', 'sunderland', '6 m'], ['blackmore', 'eng', 'loaned', 'thurrock', 'n / a'], ['jeffery', 'eng', 'loaned', 'leyton orient', 'n / a'], ['payne', 'eng', 'loaned', 'cheltenham town', 'n / a'], ['quashie', 'sco', 'loaned', 'birmingham city', 'n / a'], ['miller', 'eng', 'loaned', "bishop 's stortford", 'n / a'], ["n'gala", 'eng', 'loaned', 'mk dons', 'n / a'], ['spence', 'eng', 'loaned', 'leyton orient', 'n / a'], ['reid', 'eng', 'loaned', 'blackpool', 'n / a'], ['walker', 'eng', 'loaned', 'colchester united', 'n / a'], ['tomkins', 'eng', 'loaned', 'derby county', 'n / a'], ['stanislas', 'eng', 'loaned', 'southend', 'n / a'], ['etherington', 'eng', 'transferred', 'stoke', 'undisclosed']]

ian woosnam

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1034991-8.html.csv

unique

pga championship is the only tournament where ian woosnam never made it to the top 5 .

{'scope': 'all', 'row': '4', 'col': '3', 'col_other': '1', 'criterion': 'equal', 'value': '0', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 5', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 5 record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; top - 5 ; 0 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; top - 5 ; 0 } }', 'tointer': 'select the rows whose top - 5 record is equal to 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'top - 5', '0'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose top - 5 record is equal to 0 .', 'tostr': 'filter_eq { all_rows ; top - 5 ; 0 }'}, 'tournament'], 'result': 'pga championship', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; top - 5 ; 0 } ; tournament }'}, 'pga championship'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; top - 5 ; 0 } ; tournament } ; pga championship }', 'tointer': 'the tournament record of this unqiue row is pga championship .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; top - 5 ; 0 } } ; eq { hop { filter_eq { all_rows ; top - 5 ; 0 } ; tournament } ; pga championship } } = true', 'tointer': 'select the rows whose top - 5 record is equal to 0 . there is only one such row in the table . the tournament record of this unqiue row is pga championship .'}

and { only { filter_eq { all_rows ; top - 5 ; 0 } } ; eq { hop { filter_eq { all_rows ; top - 5 ; 0 } ; tournament } ; pga championship } } = true

select the rows whose top - 5 record is equal to 0 . there is only one such row in the table . the tournament record of this unqiue row is pga championship .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'top - 5_7': 7, '0_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'tournament_9': 9, 'pga championship_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'top - 5_7': 'top - 5', '0_8': '0', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'tournament_9': 'tournament', 'pga championship_10': 'pga championship'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'top - 5_7': [0], '0_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'tournament_9': [2], 'pga championship_10': [3]}

['tournament', 'wins', 'top - 5', 'top - 10', 'top - 25', 'events', 'cuts made']

[['masters tournament', '1', '1', '1', '7', '25', '13'], ['us open', '0', '1', '2', '4', '10', '7'], ['the open championship', '0', '4', '5', '10', '23', '17'], ['pga championship', '0', '0', '2', '3', '18', '9'], ['totals', '1', '6', '10', '24', '76', '46']]

b " grey 's anatomy ( season 4 ) "

https://en.wikipedia.org/wiki/Grey%27s_Anatomy_%28season_4%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-11058032-1.html.csv

count

shonda rhimes was one of the writers for four of the episodes in the season four series of grey 's anatomy .

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

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

eq { count { filter_eq { all_rows ; written by ; shonda rhimes } } ; 4 } = true

select the rows whose written by record fuzzily matches to shonda rhimes . 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, 'written by_5': 5, 'shonda rhimes_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', 'written by_5': 'written by', 'shonda rhimes_6': 'shonda rhimes', '4_7': '4'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'written by_5': [0], 'shonda rhimes_6': [0], '4_7': [2]}

['no in series', 'no in season', 'title', 'directed by', 'written by', 'original air date', 'us viewers ( millions )']

[['62', '1', 'a change is gon na come', 'rob corn', 'shonda rhimes', 'september 27 , 2007', '20.93'], ['63', '2', 'love / addiction', 'james frawley', 'debora cahn', 'october 4 , 2007', '18.51'], ['64', '3', 'let the truth sting', 'dan minahan', 'mark wilding', 'october 11 , 2007', '19.04'], ['65', '4', 'the heart of the matter', 'randy zisk', 'allan heinberg', 'october 18 , 2007', '18.04'], ['66', '5', 'haunt you every day', 'bethany rooney', 'krista vernoff', 'october 25 , 2007', '18.17'], ['67', '6', 'kung fu fighting', 'tom verica', 'stacy mckee', 'november 1 , 2007', '19.31'], ['68', '7', 'physical attraction , chemical reaction', 'jeff melman', 'tony phelan & joan rater', 'november 8 , 2007', '19.50'], ['69', '8', 'forever young', 'rob corn', 'mark wilding', 'november 15 , 2007', '19.61'], ['70', '9', 'crash into me ( part 1 )', 'michael grossman', 'shonda rhimes & krista vernoff', 'november 22 , 2007', '14.11'], ['71', '10', 'crash into me ( part 2 )', 'jessica yu', 'shonda rhimes & krista vernoff', 'december 6 , 2007', '17.78'], ['72', '11', 'lay your hands on me', 'john terlesky', 'allan heinberg', 'january 10 , 2008', '17.68'], ['73', '12', 'where the wild things are', 'rob corn', 'zoanne clack', 'april 24 , 2008', '16.37'], ['74', '13', 'piece of my heart', 'mark tinker', 'stacy mckee', 'may 1 , 2008', '15.31'], ['75', '14', 'the becoming', 'julie anne robinson', 'tony phelan & joan rater', 'may 8 , 2008', '16.03'], ['76', '15', 'losing my mind', 'james frawley', 'debora cahn', 'may 15 , 2008', '15.55'], ['77', '16', 'freedom ( part 1 )', 'rob corn', 'shonda rhimes', 'may 22 , 2008', '18.09']]

daniela hantuchová career statistics

https://en.wikipedia.org/wiki/Daniela_Hantuchov%C3%A1_career_statistics

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-23944006-4.html.csv

majority

daniela hantuchová was the runner-up in the majority of her tennis doubles tournaments .

{'scope': 'all', 'col': '1', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'runner - up', 'subset': None}

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

most_eq { all_rows ; outcome ; runner - up } = true

for the outcome records of all rows , most of them fuzzily match to runner - up .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'outcome_3': 3, 'runner - up_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'outcome_3': 'outcome', 'runner - up_4': 'runner - up'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'outcome_3': [0], 'runner - up_4': [0]}

['outcome', 'year', 'championship', 'surface', 'partner', 'opponents', 'score']

[['runner - up', '2002', 'berlin', 'clay', 'arantxa sánchez vicario', 'elena dementieva janette husárová', '6 - 0 , 6 - 7 , 2 - 6'], ['runner - up', '2002', 'san diego', 'hard', 'ai sugiyama', 'conchita martínez virginia ruano pascual', '7 - 6 ( 9 - 7 ) , 1 - 6 , 5 - 7'], ['runner - up', '2005', 'zurich', 'hard ( i )', 'ai sugiyama', 'cara black rennae stubbs', '7 - 6 ( 8 - 6 ) , 6 - 7 ( 4 - 7 ) , 3 - 6'], ['winner', '2006', 'rome', 'clay', 'ai sugiyama', 'elena dementieva francesca schiavone', '3 - 6 , 6 - 3 , 6 - 1'], ['runner - up', '2009', 'rome', 'clay', 'ai sugiyama', 'hsieh su - wei peng shuai', '5 - 7 , 6 - 7 ( 5 - 7 )'], ['runner - up', '2009', 'tokyo', 'hard', 'ai sugiyama', 'alisa kleybanova francesca schiavone', '4 - 6 , 2 - 6']]

indiana high school athletics conferences : allen county - metropolitan

https://en.wikipedia.org/wiki/Indiana_High_School_Athletics_Conferences%3A_Allen_County_%E2%80%93_Metropolitan

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-13986492-17.html.csv

aggregation

average enrollment in marion county indiana high schools is 3,633 .

{'scope': 'subset', 'col': '4', 'type': 'average', 'result': '3,633', 'subset': {'col': '7', 'criterion': 'fuzzily_match', 'value': 'marion'}}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'county', 'marion'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; county ; marion }', 'tointer': 'select the rows whose county record fuzzily matches to marion .'}, 'enrollment'], 'result': '3,633', 'ind': 1, 'tostr': 'avg { filter_eq { all_rows ; county ; marion } ; enrollment }'}, '3,633'], 'result': True, 'ind': 2, 'tostr': 'round_eq { avg { filter_eq { all_rows ; county ; marion } ; enrollment } ; 3,633 } = true', 'tointer': 'select the rows whose county record fuzzily matches to marion . the average of the enrollment record of these rows is 3,633 .'}

round_eq { avg { filter_eq { all_rows ; county ; marion } ; enrollment } ; 3,633 } = true

select the rows whose county record fuzzily matches to marion . the average of the enrollment record of these rows is 3,633 .

3

3

{'eq_2': 2, 'result_3': 3, 'avg_1': 1, 'filter_str_eq_0': 0, 'all_rows_4': 4, 'county_5': 5, 'marion_6': 6, 'enrollment_7': 7, '3,633_8': 8}

{'eq_2': 'eq', 'result_3': 'true', 'avg_1': 'avg', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_4': 'all_rows', 'county_5': 'county', 'marion_6': 'marion', 'enrollment_7': 'enrollment', '3,633_8': '3,633'}

{'eq_2': [3], 'result_3': [], 'avg_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'county_5': [0], 'marion_6': [0], 'enrollment_7': [1], '3,633_8': [2]}

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

[['indianapolis ben davis', 'giants', 'indianapolis', '4892', 'aaaa', 'aaaaa', '49 marion'], ['carmel', 'greyhounds', 'carmel', '4443', 'aaaa', 'aaaaa', '29 hamilton'], ['center grove', 'trojans', 'greenwood', '2.366', 'aaaa', 'aaaaa', '41 johnson'], ['lawrence north', 'wildcats', 'lawrence', '2457', 'aaaa', 'aaaaa', '49 marion'], ['indianapolis north central', 'panthers', 'indianapolis', '3492', 'aaaa', 'aaaaa', '49 marion'], ['terre haute north', 'patriots', 'terre haute', '2083', 'aaaa', 'aaaaa', '84 vigo'], ['terre haute south', 'braves', 'terre haute', '1829', 'aaaa', 'aaaaa', '84 vigo'], ['indianapolis warren central', 'warriors', 'indianapolis', '3691', 'aaaa', 'aaaaa', '49 marion']]

nick park

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-149052-1.html.csv

majority

the majority of nick park 's works are classified as short films .

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

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

most_eq { all_rows ; notes ; short film } = true

for the notes records of all rows , most of them fuzzily match to short film .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'notes_3': 3, 'short film_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'notes_3': 'notes', 'short film_4': 'short film'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'notes_3': [0], 'short film_4': [0]}

['year', 'title', 'director', 'writer', 'notes']

[['1989', 'creature comforts', 'yes', 'yes', 'short film'], ['1989', 'wallace & gromit : a grand day out', 'yes', 'yes', 'short film'], ['1993', 'wallace & gromit : the wrong trousers', 'yes', 'yes', 'short film'], ['1995', 'wallace & gromit : a close shave', 'yes', 'yes', 'short film'], ['2000', 'chicken run', 'yes', 'yes', 'co - directed with peter lord'], ['2005', 'wallace & gromit : the curse of the were - rabbit', 'yes', 'yes', 'co - directed with steve box'], ['2008', 'wallace & gromit : a matter of loaf and death', 'yes', 'yes', 'short film']]

lukoil

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1027881-2.html.csv

unique

lukoil - permnefteorgsintez is the only one among those launched in 1958 that has a capacity , mln tpa of 12 , 0 .

{'scope': 'subset', 'row': '2', 'col': '5', 'col_other': '1,3', 'criterion': 'equal', 'value': '12 , 0', 'subset': {'col': '3', 'criterion': 'equal', 'value': '1958'}}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'launched', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launched ; 1958 }', 'tointer': 'select the rows whose launched record is equal to 1958 .'}, 'capacity , mln tpa', '12 , 0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } }', 'tointer': 'select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'launched', '1958'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; launched ; 1958 }', 'tointer': 'select the rows whose launched record is equal to 1958 .'}, 'capacity , mln tpa', '12 , 0'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 .', 'tostr': 'filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 }'}, 'name'], 'result': 'lukoil - permnefteorgsintez', 'ind': 3, 'tostr': 'hop { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } ; name }'}, 'lukoil - permnefteorgsintez'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } ; name } ; lukoil - permnefteorgsintez }', 'tointer': 'the name record of this unqiue row is lukoil - permnefteorgsintez .'}], 'result': True, 'ind': 5, 'tostr': 'and { only { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } ; name } ; lukoil - permnefteorgsintez } } = true', 'tointer': 'select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 . there is only one such row in the table . the name record of this unqiue row is lukoil - permnefteorgsintez .'}

and { only { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } } ; eq { hop { filter_eq { filter_eq { all_rows ; launched ; 1958 } ; capacity , mln tpa ; 12 , 0 } ; name } ; lukoil - permnefteorgsintez } } = true

select the rows whose launched record is equal to 1958 . among these rows , select the rows whose capacity , mln tpa record fuzzily matches to 12 , 0 . there is only one such row in the table . the name record of this unqiue row is lukoil - permnefteorgsintez .

8

6

{'and_5': 5, 'result_6': 6, 'only_2': 2, 'filter_str_eq_1': 1, 'filter_eq_0': 0, 'all_rows_7': 7, 'launched_8': 8, '1958_9': 9, 'capacity , mln tpa_10': 10, '12 , 0_11': 11, 'str_eq_4': 4, 'str_hop_3': 3, 'name_12': 12, 'lukoil - permnefteorgsintez_13': 13}

{'and_5': 'and', 'result_6': 'true', 'only_2': 'only', 'filter_str_eq_1': 'filter_str_eq', 'filter_eq_0': 'filter_eq', 'all_rows_7': 'all_rows', 'launched_8': 'launched', '1958_9': '1958', 'capacity , mln tpa_10': 'capacity , mln tpa', '12 , 0_11': '12 , 0', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'name_12': 'name', 'lukoil - permnefteorgsintez_13': 'lukoil - permnefteorgsintez'}

{'and_5': [6], 'result_6': [], 'only_2': [5], 'filter_str_eq_1': [2, 3], 'filter_eq_0': [1], 'all_rows_7': [0], 'launched_8': [0], '1958_9': [0], 'capacity , mln tpa_10': [1], '12 , 0_11': [1], 'str_eq_4': [5], 'str_hop_3': [4], 'name_12': [3], 'lukoil - permnefteorgsintez_13': [4]}

['name', 'location', 'launched', 'acquired', 'capacity , mln tpa']

[['lukoil - nizhegorodnefteorgsintez', 'kstovo', '1958', '2000', '15 , 0'], ['lukoil - permnefteorgsintez', 'perm', '1958', '1991', '12 , 0'], ['lukoil - volgogradneftepererabotka', 'volgograd', '1957', '1991', '9 , 9'], ['lukoil - ukhtaneftepererabotka', 'ukhta', '1934', '2000', '3 , 7'], ['lukoil - odessky neftepererabatyvayuschiy zavod', 'odessa', '1937', '1999', '3 , 6'], ['lukoil neftochim burgas', 'burgas', '1964', '1999', '7 , 5'], ['petrotel - lukoil', 'ploieåÿti', '1904', '1998', '2 , 4'], ['isab', 'priolo gargallo', '1975', '2008', '16 , 0'], ['trn', 'vlissingen', '1973', '2009', '7 , 9']]

1980 - 81 philadelphia flyers season

https://en.wikipedia.org/wiki/1980%E2%80%9381_Philadelphia_Flyers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14311305-4.html.csv

unique

game number 32 was the only game to have 47 points .

{'scope': 'all', 'row': '6', 'col': '6', 'col_other': '1', 'criterion': 'equal', 'value': '47', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '47'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 47 .', 'tostr': 'filter_eq { all_rows ; points ; 47 }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; points ; 47 } }', 'tointer': 'select the rows whose points record is equal to 47 . there is only one such row in the table .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'points', '47'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose points record is equal to 47 .', 'tostr': 'filter_eq { all_rows ; points ; 47 }'}, 'game'], 'result': '32', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; points ; 47 } ; game }'}, '32'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; points ; 47 } ; game } ; 32 }', 'tointer': 'the game record of this unqiue row is 32 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; points ; 47 } } ; eq { hop { filter_eq { all_rows ; points ; 47 } ; game } ; 32 } } = true', 'tointer': 'select the rows whose points record is equal to 47 . there is only one such row in the table . the game record of this unqiue row is 32 .'}

and { only { filter_eq { all_rows ; points ; 47 } } ; eq { hop { filter_eq { all_rows ; points ; 47 } ; game } ; 32 } } = true

select the rows whose points record is equal to 47 . there is only one such row in the table . the game record of this unqiue row is 32 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_eq_0': 0, 'all_rows_6': 6, 'points_7': 7, '47_8': 8, 'eq_3': 3, 'num_hop_2': 2, 'game_9': 9, '32_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_eq_0': 'filter_eq', 'all_rows_6': 'all_rows', 'points_7': 'points', '47_8': '47', 'eq_3': 'eq', 'num_hop_2': 'num_hop', 'game_9': 'game', '32_10': '32'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_eq_0': [1, 2], 'all_rows_6': [0], 'points_7': [0], '47_8': [0], 'eq_3': [4], 'num_hop_2': [3], 'game_9': [2], '32_10': [3]}

['game', 'december', 'opponent', 'score', 'record', 'points']

[['27', '4', 'chicago black hawks', '7 - 5', '18 - 5 - 4', '40'], ['28', '6', 'detroit red wings', '2 - 4', '18 - 6 - 4', '40'], ['29', '7', 'colorado rockies', '4 - 2', '19 - 6 - 4', '42'], ['30', '10', 'chicago black hawks', '2 - 2', '19 - 6 - 5', '43'], ['31', '13', 'pittsburgh penguins', '6 - 5', '20 - 6 - 5', '45'], ['32', '14', 'st louis blues', '5 - 4', '21 - 6 - 5', '47'], ['33', '18', 'colorado rockies', '2 - 0', '22 - 6 - 5', '49'], ['34', '20', 'washington capitals', '5 - 2', '23 - 6 - 5', '51'], ['35', '21', 'washington capitals', '0 - 6', '23 - 7 - 5', '51'], ['36', '27', 'calgary flames', '1 - 2', '23 - 8 - 5', '51'], ['37', '28', 'edmonton oilers', '2 - 1', '24 - 8 - 5', '53'], ['38', '30', 'minnesota north stars', '5 - 6', '24 - 9 - 5', '53']]

sebastián gonzález

https://en.wikipedia.org/wiki/Sebasti%C3%A1n_Gonz%C3%A1lez

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1257826-1.html.csv

count

there were six goals scored by sebastian gonzales .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '1', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'goal'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose goal record is arbitrary .', 'tostr': 'filter_all { all_rows ; goal }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; goal } }', 'tointer': 'select the rows whose goal record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; goal } } ; 6 } = true', 'tointer': 'select the rows whose goal record is arbitrary . the number of such rows is 6 .'}

eq { count { filter_all { all_rows ; goal } } ; 6 } = true

select the rows whose goal record is arbitrary . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'goal_5': 5, '6_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'goal_5': 'goal', '6_6': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'goal_5': [0], '6_6': [2]}

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

[['1', '17 january 2001', '2 - 0', '2 - 0', 'friendly'], ['2', '20 january 2001', '1 - 0', '2 - 0', 'friendly'], ['3', '20 january 2001', '2 - 0', '2 - 0', 'friendly'], ['4', '15 march 2001', '3 - 1', '3 - 1', 'friendly'], ['5', '14 july 2004', '0 - 1', '1 - 1', '2004 copa américa'], ['6', '17 november 2004', '2 - 1', '2 - 1', 'friendly']]

memphis grizzlies all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-16494599-4.html.csv

ordinal

terry dehere has the third highest player number on the memphis grizzlies all - time roster .

{'row': '5', 'col': '2', 'order': '3', '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', 'no', '3'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; no ; 3 }'}, 'player'], 'result': 'terry dehere', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; no ; 3 } ; player }'}, 'terry dehere'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; no ; 3 } ; player } ; terry dehere } = true', 'tointer': 'select the row whose no record of all rows is 3rd maximum . the player record of this row is terry dehere .'}

eq { hop { nth_argmax { all_rows ; no ; 3 } ; player } ; terry dehere } = true

select the row whose no record of all rows is 3rd maximum . the player record of this row is terry dehere .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'no_5': 5, '3_6': 6, 'player_7': 7, 'terry dehere_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', 'no_5': 'no', '3_6': '3', 'player_7': 'player', 'terry dehere_8': 'terry dehere'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'no_5': [0], '3_6': [0], 'player_7': [1], 'terry dehere_8': [2]}

['player', 'no', 'nationality', 'position', 'years for grizzlies', 'school / club team']

[['antonio daniels', '33', 'united states', 'point guard', '1997 - 1998', 'bowling green'], ['ed davis', '32', 'united states', 'forward', '2013 - present', 'north carolina'], ['josh davis', '18', 'united states', 'forward', '2011 - 2012', 'wyoming'], ['austin daye', '5', 'united states', 'small forward', '2013 - present', 'gonzaga'], ['terry dehere', '24', 'united states', 'guard', '1999', 'seton hall'], ['michael dickerson', '8', 'united states', 'guard - forward', '1999 - 2003', 'arizona']]

kairat nurdauletov

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12706952-1.html.csv

count

kairat nurdauletov participated in 3 friendly competitions between 2007 and 2012 .

{'scope': 'all', 'criterion': 'equal', 'value': 'friendly', 'result': '3', 'col': '5', 'subset': None}

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

eq { count { filter_eq { all_rows ; competition ; friendly } } ; 3 } = true

select the rows whose competition record fuzzily matches to friendly . 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, 'competition_5': 5, 'friendly_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', 'competition_5': 'competition', 'friendly_6': 'friendly', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'competition_5': [0], 'friendly_6': [0], '3_7': [2]}

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

[['8 september 2007', 'central stadium , almaty , kazakhstan', '1 - 1', 'draw', 'friendly'], ['7 october 2011', 'king baudouin stadium , almaty , kazakhstan', '4 - 1', 'lost', 'friendly'], ['1 june 2012', 'central stadium , almaty , kazakhstan', '5 - 2', 'win', 'friendly'], ['7 september 2012', 'astana arena , astana , kazakhstan', '1 - 2', 'loss', 'world cup 2014 qualilfier'], ['6 september 2013', 'astana arena , astana , kazakhstan', '2 - 1', 'win', 'world cup 2014 qualilfier']]

lara gut

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15556757-2.html.csv

unique

the only time lara gut was at a race in italy was on january 23 , 2011 .

{'scope': 'all', 'row': '6', 'col': '3', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'italy', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; location ; italy }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; location ; italy } }', 'tointer': 'select the rows whose location record fuzzily matches to italy . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'italy'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose location record fuzzily matches to italy .', 'tostr': 'filter_eq { all_rows ; location ; italy }'}, 'date'], 'result': '23 jan 2011', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; location ; italy } ; date }'}, '23 jan 2011'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; location ; italy } ; date } ; 23 jan 2011 }', 'tointer': 'the date record of this unqiue row is 23 jan 2011 .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; location ; italy } } ; eq { hop { filter_eq { all_rows ; location ; italy } ; date } ; 23 jan 2011 } } = true', 'tointer': 'select the rows whose location record fuzzily matches to italy . there is only one such row in the table . the date record of this unqiue row is 23 jan 2011 .'}

and { only { filter_eq { all_rows ; location ; italy } } ; eq { hop { filter_eq { all_rows ; location ; italy } ; date } ; 23 jan 2011 } } = true

select the rows whose location record fuzzily matches to italy . there is only one such row in the table . the date record of this unqiue row is 23 jan 2011 .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'location_7': 7, 'italy_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'date_9': 9, '23 jan 2011_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'location_7': 'location', 'italy_8': 'italy', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'date_9': 'date', '23 jan 2011_10': '23 jan 2011'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'location_7': [0], 'italy_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'date_9': [2], '23 jan 2011_10': [3]}

['season', 'date', 'location', 'race', 'place']

[['2008', '2 feb 2008', 'st moritz , switzerland', 'downhill', '3rd'], ['2009', '20 dec 2008', 'st moritz , switzerland', 'super - g', '1st'], ['2009', '28 dec 2008', 'semmering , austria', 'giant slalom', '3rd'], ['2011', '18 dec 2010', "val d'isère , france", 'downhill', '3rd'], ['2011', '9 jan 2011', 'altenmarkt - zauchensee , austria', 'super - g', '1st'], ['2011', '23 jan 2011', "cortina d'ampezzo , italy", 'super - g', '3rd'], ['2011', '16 mar 2011', 'lenzerheide , switzerland', 'downhill', '2nd'], ['2013', '14 dec 2012', "val - d'isère , france", 'downhill', '1st'], ['2013', '17 mar 2013', 'lenzerheide , switzerland', 'giant slalom', '3rd'], ['2014', '26 oct 2013', 'sölden , austria', 'giant slalom', '1st']]

list of kraft nabisco championship champions

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27864661-6.html.csv

ordinal

the number one ranked nation on the list of kraft nabisco championship champions had the highest number of major wins among the other nations .

{'row': '1', 'col': '6', 'order': '1', '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', 'major winners', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; major winners ; 1 }'}, 'rank'], 'result': '1', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; major winners ; 1 } ; rank }'}, '1'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; major winners ; 1 } ; rank } ; 1 } = true', 'tointer': 'select the row whose major winners record of all rows is 1st maximum . the rank record of this row is 1 .'}

eq { hop { nth_argmax { all_rows ; major winners ; 1 } ; rank } ; 1 } = true

select the row whose major winners record of all rows is 1st maximum . the rank record of this row is 1 .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'major winners_5': 5, '1_6': 6, 'rank_7': 7, '1_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', 'major winners_5': 'major winners', '1_6': '1', 'rank_7': 'rank', '1_8': '1'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'major winners_5': [0], '1_6': [0], 'rank_7': [1], '1_8': [2]}

['rank', 'nationality', 'non - major wins', 'non - major winners', 'major wins', 'major winners', 'total wins', 'total winners', 'first title', 'last title']

[['1', 'united states', '8', '8', '19', '13', '27', '21', '1972', '2011'], ['2', 'sweden', '0', '0', '4', '2', '4', '2', '1993', '2005'], ['3', 'south korea', '0', '0', '3', '3', '3', '3', '2004', '2013'], ['t4', 'australia', '0', '0', '2', '1', '2', '1', '2000', '2006'], ['t4', 'canada', '2', '1', '0', '0', '2', '1', '1978', '1979'], ['t6', 'france', '0', '0', '1', '1', '1', '1', '2003', '2003'], ['t6', 'mexico', '0', '0', '1', '1', '1', '1', '2008', '2008'], ['t6', 'south africa', '1', '1', '0', '0', '1', '1', '1982', '1982']]

ranked lists of chilean regions

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25042332-22.html.csv

comparative

the arica and parinacota chilean region has a higher tertiary education attainment than the maule region .

{'row_1': '1', 'row_2': '9', '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', 'region', 'arica and parinacota'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose region record fuzzily matches to arica and parinacota .', 'tostr': 'filter_eq { all_rows ; region ; arica and parinacota }'}, 'tertiary ( 18 - 24 years )'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; region ; arica and parinacota } ; tertiary ( 18 - 24 years ) }', 'tointer': 'select the rows whose region record fuzzily matches to arica and parinacota . take the tertiary ( 18 - 24 years ) record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'region', 'maule'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose region record fuzzily matches to maule .', 'tostr': 'filter_eq { all_rows ; region ; maule }'}, 'tertiary ( 18 - 24 years )'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; region ; maule } ; tertiary ( 18 - 24 years ) }', 'tointer': 'select the rows whose region record fuzzily matches to maule . take the tertiary ( 18 - 24 years ) record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; region ; arica and parinacota } ; tertiary ( 18 - 24 years ) } ; hop { filter_eq { all_rows ; region ; maule } ; tertiary ( 18 - 24 years ) } } = true', 'tointer': 'select the rows whose region record fuzzily matches to arica and parinacota . take the tertiary ( 18 - 24 years ) record of this row . select the rows whose region record fuzzily matches to maule . take the tertiary ( 18 - 24 years ) record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; region ; arica and parinacota } ; tertiary ( 18 - 24 years ) } ; hop { filter_eq { all_rows ; region ; maule } ; tertiary ( 18 - 24 years ) } } = true

select the rows whose region record fuzzily matches to arica and parinacota . take the tertiary ( 18 - 24 years ) record of this row . select the rows whose region record fuzzily matches to maule . take the tertiary ( 18 - 24 years ) 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, 'region_7': 7, 'arica and parinacota_8': 8, 'tertiary (18 - 24 years)_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'region_11': 11, 'maule_12': 12, 'tertiary (18 - 24 years)_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', 'region_7': 'region', 'arica and parinacota_8': 'arica and parinacota', 'tertiary (18 - 24 years)_9': 'tertiary ( 18 - 24 years )', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'region_11': 'region', 'maule_12': 'maule', 'tertiary (18 - 24 years)_13': 'tertiary ( 18 - 24 years )'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'region_7': [0], 'arica and parinacota_8': [0], 'tertiary (18 - 24 years)_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'region_11': [1], 'maule_12': [1], 'tertiary (18 - 24 years)_13': [3]}

['region', 'preschool ( 0 - 5 years )', 'primary ( 6 - 13 years )', 'secondary ( 14 - 17 years )', 'tertiary ( 18 - 24 years )']

[['arica and parinacota', '42.92', '91.17', '76.65', '38.67'], ['tarapacá', '47.51', '94.52', '70.82', '28.16'], ['antofagasta', '38.13', '91.90', '70.78', '28.26'], ['atacama', '38.14', '94.13', '73.93', '23.01'], ['coquimbo', '47.43', '93.00', '68.95', '33.89'], ['valparaíso', '50.23', '91.37', '71.63', '42.96'], ['santiago', '43.15', '92.38', '72.91', '35.03'], ["o'higgins", '41.89', '95.41', '63.00', '28.60'], ['maule', '43.38', '93.10', '67.49', '26.31'], ['biobío', '40.76', '93.45', '71.83', '31.62'], ['araucanía', '45.49', '93.40', '73.25', '29.55'], ['los ríos', '38.49', '94.18', '69.83', '33.88'], ['los lagos', '40.42', '92.88', '71.43', '25.78'], ['aisén', '52.28', '94.39', '69.30', '22.42'], ['magallanes', '51.16', '94.40', '72.50', '43.87']]

89th united states congress

https://en.wikipedia.org/wiki/89th_United_States_Congress

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1847180-3.html.csv

unique

ross bass was the only vacator of the 89th united states congress who had no successor .

{'scope': 'all', 'row': '6', 'col': '4', 'col_other': '2', 'criterion': 'fuzzily_match', 'value': 'vacant', 'subset': None}

{'func': 'and', 'args': [{'func': 'only', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; successor ; vacant }'}], 'result': True, 'ind': 1, 'tostr': 'only { filter_eq { all_rows ; successor ; vacant } }', 'tointer': 'select the rows whose successor record fuzzily matches to vacant . there is only one such row in the table .'}, {'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'successor', 'vacant'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose successor record fuzzily matches to vacant .', 'tostr': 'filter_eq { all_rows ; successor ; vacant }'}, 'vacator'], 'result': 'ross bass ( d )', 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; successor ; vacant } ; vacator }'}, 'ross bass ( d )'], 'result': True, 'ind': 3, 'tostr': 'eq { hop { filter_eq { all_rows ; successor ; vacant } ; vacator } ; ross bass ( d ) }', 'tointer': 'the vacator record of this unqiue row is ross bass ( d ) .'}], 'result': True, 'ind': 4, 'tostr': 'and { only { filter_eq { all_rows ; successor ; vacant } } ; eq { hop { filter_eq { all_rows ; successor ; vacant } ; vacator } ; ross bass ( d ) } } = true', 'tointer': 'select the rows whose successor record fuzzily matches to vacant . there is only one such row in the table . the vacator record of this unqiue row is ross bass ( d ) .'}

and { only { filter_eq { all_rows ; successor ; vacant } } ; eq { hop { filter_eq { all_rows ; successor ; vacant } ; vacator } ; ross bass ( d ) } } = true

select the rows whose successor record fuzzily matches to vacant . there is only one such row in the table . the vacator record of this unqiue row is ross bass ( d ) .

6

5

{'and_4': 4, 'result_5': 5, 'only_1': 1, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'successor_7': 7, 'vacant_8': 8, 'str_eq_3': 3, 'str_hop_2': 2, 'vacator_9': 9, 'ross bass (d)_10': 10}

{'and_4': 'and', 'result_5': 'true', 'only_1': 'only', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'successor_7': 'successor', 'vacant_8': 'vacant', 'str_eq_3': 'str_eq', 'str_hop_2': 'str_hop', 'vacator_9': 'vacator', 'ross bass (d)_10': 'ross bass ( d )'}

{'and_4': [5], 'result_5': [], 'only_1': [4], 'filter_str_eq_0': [1, 2], 'all_rows_6': [0], 'successor_7': [0], 'vacant_8': [0], 'str_eq_3': [4], 'str_hop_2': [3], 'vacator_9': [2], 'ross bass (d)_10': [3]}

['state ( class )', 'vacator', 'reason for change', 'successor', "date of successor 's formal installation"]

[['south carolina ( 3 )', 'olin d johnston ( d )', 'died april 18 , 1965', 'donald s russell ( d )', 'april 22 , 1965'], ['south carolina ( 3 )', 'donald s russell ( d )', 'successor elected november 8 , 1965', 'ernest hollings ( d )', 'november 9 , 1965'], ['virginia ( 1 )', 'harry f byrd ( d )', 'resigned november 10 , 1965', 'harry f byrd , jr ( d )', 'november 12 , 1965'], ['michigan ( 2 )', 'patrick v mcnamara ( d )', 'died april 30 , 1966', 'robert p griffin ( r )', 'may 11 , 1966'], ['virginia ( 2 )', 'a willis robertson ( d )', 'resigned december 30 , 1966', 'william b spong , jr ( d )', 'december 31 , 1966'], ['tennessee ( 2 )', 'ross bass ( d )', 'resigned january 2 , 1967', 'vacant', 'not filled this term']]

2003 grand prix of monterey

https://en.wikipedia.org/wiki/2003_Grand_Prix_of_Monterey

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18805166-2.html.csv

count

8 of the drivers completed 87 or more laps .

{'scope': 'all', 'criterion': 'greater_than_eq', 'value': '87', 'result': '8', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_greater_eq', 'args': ['all_rows', 'laps', '87'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is greater than or equal to 87 .', 'tostr': 'filter_greater_eq { all_rows ; laps ; 87 }'}], 'result': '8', 'ind': 1, 'tostr': 'count { filter_greater_eq { all_rows ; laps ; 87 } }', 'tointer': 'select the rows whose laps record is greater than or equal to 87 . the number of such rows is 8 .'}, '8'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_greater_eq { all_rows ; laps ; 87 } } ; 8 } = true', 'tointer': 'select the rows whose laps record is greater than or equal to 87 . the number of such rows is 8 .'}

eq { count { filter_greater_eq { all_rows ; laps ; 87 } } ; 8 } = true

select the rows whose laps record is greater than or equal to 87 . the number of such rows is 8 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_greater_eq_0': 0, 'all_rows_4': 4, 'laps_5': 5, '87_6': 6, '8_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_greater_eq_0': 'filter_greater_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '87_6': '87', '8_7': '8'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_greater_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '87_6': [0], '8_7': [2]}

['driver', 'team', 'laps', 'time / retired', 'grid', 'points']

[['patrick carpentier', "team player 's", '87', '1:48:11.023', '1', '22'], ['bruno junqueira', 'newman / haas racing', '87', '+ 0.8 secs', '2', '17'], ['paul tracy', "team player 's", '87', '+ 28.6 secs', '3', '14'], ['michel jourdain , jr', 'team rahal', '87', '+ 40.8 secs', '13', '12'], ['mario haberfeld', 'mi - jack conquest racing', '87', '+ 42.1 secs', '6', '10'], ['oriol servià', 'patrick racing', '87', '+ 1:00.2', '10', '8'], ['adrian fernández', 'fernández racing', '87', '+ 1:01.4', '5', '6'], ['jimmy vasser', 'american spirit team johansson', '87', '+ 1:01.8', '8', '5'], ['tiago monteiro', 'fittipaldi - dingman racing', '86', '+ 1 lap', '15', '4'], ['mario domínguez', 'herdez competition', '86', '+ 1 lap', '11', '3'], ['bryan herta', 'pk racing', '86', '+ 1 lap', '12', '2'], ['ryan hunter - reay', 'american spirit team johansson', '86', '+ 1 lap', '17', '1'], ['joël camathias', 'dale coyne racing', '85', '+ 2 laps', '18', '0'], ['alex tagliani', 'rocketsports racing', '85', '+ 2 laps', '14', '0'], ['roberto moreno', 'herdez competition', '85', '+ 2 laps', '9', '0'], ['geoff boss', 'dale coyne racing', '83', 'mechanical', '19', '0'], ['sébastien bourdais', 'newman / haas racing', '77', 'mechanical', '4', '0'], ['darren manning', 'walker racing', '12', 'mechanical', '7', '0'], ['rodolfo lavín', 'walker racing', '10', 'mechanical', '16', '0']]

fiba under - 19 world championship

https://en.wikipedia.org/wiki/FIBA_Under-19_World_Championship

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11383852-2.html.csv

aggregation

in fiba under - 19 world championship there are people got totally 25 medals that includes all the silver , gold and bronze medals .

{'scope': 'all', 'col': '5', 'type': 'sum', 'result': '25', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'total'], 'result': '25', 'ind': 0, 'tostr': 'sum { all_rows ; total }'}, '25'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; total } ; 25 } = true', 'tointer': 'the sum of the total record of all rows is 25 .'}

round_eq { sum { all_rows ; total } ; 25 } = true

the sum of the total record of all rows is 25 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'total_4': 4, '25_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'total_4': 'total', '25_5': '25'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'total_4': [0], '25_5': [1]}

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

[['1', '5', '3', '0', '8'], ['2', '2', '2', '0', '4'], ['3', '1', '1', '1', '3'], ['5', '1', '1', '0', '2'], ['6', '1', '0', '1', '2'], ['8', '0', '1', '1', '2'], ['10', '0', '1', '0', '1'], ['11', '0', '0', '2', '2'], ['13', '0', '0', '1', '1']]

1969 cleveland browns season

https://en.wikipedia.org/wiki/1969_Cleveland_Browns_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10652161-2.html.csv

count

there were two games in the browns season of 1969 with less than 35000 fans in attendance .

{'scope': 'all', 'criterion': 'less_than', 'value': '35000', 'result': '2', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_less', 'args': ['all_rows', 'attendance', '35000'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose attendance record is less than 35000 .', 'tostr': 'filter_less { all_rows ; attendance ; 35000 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_less { all_rows ; attendance ; 35000 } }', 'tointer': 'select the rows whose attendance record is less than 35000 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_less { all_rows ; attendance ; 35000 } } ; 2 } = true', 'tointer': 'select the rows whose attendance record is less than 35000 . the number of such rows is 2 .'}

eq { count { filter_less { all_rows ; attendance ; 35000 } } ; 2 } = true

select the rows whose attendance record is less than 35000 . the number of such rows is 2 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_less_0': 0, 'all_rows_4': 4, 'attendance_5': 5, '35000_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_less_0': 'filter_less', 'all_rows_4': 'all_rows', 'attendance_5': 'attendance', '35000_6': '35000', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_less_0': [1], 'all_rows_4': [0], 'attendance_5': [0], '35000_6': [0], '2_7': [2]}

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

[['1', 'august 10 , 1969', 'san francisco 49ers at seattle', 'w 24 - 19', '32219'], ['2', 'august 16 , 1969', 'los angeles rams', 'w 10 - 3', '54937'], ['3', 'august 23 , 1969', 'san diego chargers', 't 19 - 19', '36005'], ['4', 'august 30 , 1969', 'green bay packers', 'l 27 - 17', '85532'], ['5', 'september 6 , 1969', 'washington redskins', 'w 20 - 10', '45994'], ['6', 'september 13 , 1969', 'minnesota vikings at akron', 'l 23 - 16', '28561']]

washington redskins draft history

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17100961-50.html.csv

superlative

in the washington redskins draft history , art monk ranks as the highest overall .

{'scope': 'all', 'col_superlative': '3', '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', 'overall'], 'result': None, 'ind': 0, 'tostr': 'argmin { all_rows ; overall }'}, 'name'], 'result': 'art monk', 'ind': 1, 'tostr': 'hop { argmin { all_rows ; overall } ; name }'}, 'art monk'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmin { all_rows ; overall } ; name } ; art monk } = true', 'tointer': 'select the row whose overall record of all rows is minimum . the name record of this row is art monk .'}

eq { hop { argmin { all_rows ; overall } ; name } ; art monk } = true

select the row whose overall record of all rows is minimum . the name record of this row is art monk .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'overall_5': 5, 'name_6': 6, 'art monk_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'overall_5': 'overall', 'name_6': 'name', 'art monk_7': 'art monk'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'overall_5': [0], 'name_6': [1], 'art monk_7': [2]}

['round', 'pick', 'overall', 'name', 'position', 'college']

[['1', '18', '18', 'art monk', 'wr', 'syracuse'], ['2', '27', '55', 'mat mendenhall', 'de', 'brigham young'], ['6', '17', '155', 'farley bell', 'lb', 'cincinnati'], ['7', '22', '187', 'melvin jones', 'g', 'houston'], ['9', '20', '241', 'lawrence mccullough', 'wr', 'illinois'], ['10', '19', '268', 'lewis walker', 'rb', 'utah'], ['11', '18', '295', 'mike matocha', 'de', 'texas - arlington'], ['12', '22', '327', 'marcene emmett', 'db', 'north alabama']]

list of bangladeshi submissions for the academy award for best foreign language film

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-17156199-1.html.csv

ordinal

humayun ahmed is the director of the 2nd earliest best foreign language film for the bangladeshi submission award .

{'row': '2', 'col': '1', 'order': '2', 'col_other': '4', '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', 'year ( ceremony )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmin { all_rows ; year ( ceremony ) ; 2 }'}, 'director'], 'result': 'humayun ahmed', 'ind': 1, 'tostr': 'hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director }'}, 'humayun ahmed'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director } ; humayun ahmed } = true', 'tointer': 'select the row whose year ( ceremony ) record of all rows is 2nd minimum . the director record of this row is humayun ahmed .'}

eq { hop { nth_argmin { all_rows ; year ( ceremony ) ; 2 } ; director } ; humayun ahmed } = true

select the row whose year ( ceremony ) record of all rows is 2nd minimum . the director record of this row is humayun ahmed .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmin_0': 0, 'all_rows_4': 4, 'year (ceremony)_5': 5, '2_6': 6, 'director_7': 7, 'humayun ahmed_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', 'year (ceremony)_5': 'year ( ceremony )', '2_6': '2', 'director_7': 'director', 'humayun ahmed_8': 'humayun ahmed'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmin_0': [1], 'all_rows_4': [0], 'year (ceremony)_5': [0], '2_6': [0], 'director_7': [1], 'humayun ahmed_8': [2]}

['year ( ceremony )', 'film title used in nomination', 'original title', 'director', 'result']

[['2002 ( 75th )', 'the clay bird', 'মাটির ময়না ( matir moyna )', 'tareque masud', 'not nominated'], ['2005 ( 78th )', 'shyamol chhaya', 'শ্যামল ছায়া ( shyamol chhaya )', 'humayun ahmed', 'not nominated'], ['2006 ( 79th )', 'forever flows', 'নিরন্তর ( nirontor )', 'abu sayeed', 'not nominated'], ['2007 ( 80th )', 'on the wings of dreams', 'স্বপ্নডানায় ( swopnodanay )', 'golam rabbany biplob', 'not nominated'], ['2008 ( 81st )', 'aha !', 'আহা ! ( aha )', 'enamul karim nirjhar', 'not nominated'], ['2009 ( 82nd )', 'beyond the circle', 'বৃত্তের বাইরে ( britter baire )', 'golam rabbany biplob', 'not nominated'], ['2012 ( 85th )', 'ghetuputra kamola', '( ghetuputra kamola )', 'humayun ahmed', 'not nominated']]

taylor dent

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1551815-5.html.csv

ordinal

taylor dent 's second to last tournament was in adelaide , australia .

{'row': '6', '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', 'date ( final )', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; date ( final ) ; 2 }'}, 'tournament'], 'result': 'adelaide , australia', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; date ( final ) ; 2 } ; tournament }'}, 'adelaide , australia'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; date ( final ) ; 2 } ; tournament } ; adelaide , australia } = true', 'tointer': 'select the row whose date ( final ) record of all rows is 2nd maximum . the tournament record of this row is adelaide , australia .'}

eq { hop { nth_argmax { all_rows ; date ( final ) ; 2 } ; tournament } ; adelaide , australia } = true

select the row whose date ( final ) record of all rows is 2nd maximum . the tournament record of this row is adelaide , australia .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'date (final)_5': 5, '2_6': 6, 'tournament_7': 7, 'adelaide , australia_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', 'date (final)_5': 'date ( final )', '2_6': '2', 'tournament_7': 'tournament', 'adelaide , australia_8': 'adelaide , australia'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'date (final)_5': [0], '2_6': [0], 'tournament_7': [1], 'adelaide , australia_8': [2]}

['outcome', 'date ( final )', 'tournament', 'surface', 'opponent in the final', 'score']

[['winner', 'july 7 2002', 'newport , united states', 'grass', 'james blake', '6 - 1 , 4 - 6 , 6 - 4'], ['winner', 'february 17 , 2003', 'memphis , united states', 'hard ( i )', 'andy roddick', '6 - 1 , 6 - 4'], ['winner', 'september 22 , 2003', 'bangkok , thailand', 'hard ( i )', 'juan carlos ferrero', '6 - 3 , 7 - 6 ( 7 - 5 )'], ['winner', 'september 29 2003', 'moscow , russia', 'carpet ( i )', 'sargis sargsian', '7 - 6 ( 7 - 5 ) , 6 - 4'], ['runner - up', 'october 10 , 2004', 'tokyo , japan', 'hard', 'jiří novák', '7 - 5 , 1 - 6 , 3 - 6'], ['runner - up', 'january 9 2005', 'adelaide , australia', 'hard', 'joachim johansson', '5 - 7 , 3 - 6'], ['runner - up', 'july 24 2005', 'indianapolis , united states', 'hard', 'robby ginepri', '6 - 4 , 3 - 6 , 0 - 3 , ret']]

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

majority

the majority of versions of the porsche boxster listed produce less than 200 g/km of carbon dioxide .

{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'less_than_eq', 'value': '200 g/km', 'subset': None}

{'func': 'most_less_eq', 'args': ['all_rows', 'co2', '200 g/km'], 'result': True, 'ind': 0, 'tointer': 'for the co2 records of all rows , most of them are less than or equal to 200 g/km .', 'tostr': 'most_less_eq { all_rows ; co2 ; 200 g/km } = true'}

most_less_eq { all_rows ; co2 ; 200 g/km } = true

for the co2 records of all rows , most of them are less than or equal to 200 g/km .

1

1

{'most_less_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'co2_3': 3, '200 g/km_4': 4}

{'most_less_eq_0': 'most_less_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'co2_3': 'co2', '200 g/km_4': '200 g/km'}

{'most_less_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'co2_3': [0], '200 g/km_4': [0]}

['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']]

blue ridge hockey conference

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16404837-5.html.csv

comparative

in the blue ridge hockey conference , high point university was founded 30 years before coastal carolina university .

{'row_1': '3', 'row_2': '2', 'col': '3', 'col_other': '1', 'relation': 'diff', 'record_mentioned': 'no', 'diff_result': {'diff_value': '30', 'bigger': 'row2'}}

{'func': 'eq', 'args': [{'func': 'diff', 'args': [{'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'high point university'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose school record fuzzily matches to high point university .', 'tostr': 'filter_eq { all_rows ; school ; high point university }'}, 'founded'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; school ; high point university } ; founded }', 'tointer': 'select the rows whose school record fuzzily matches to high point university . take the founded record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'school', 'coastal carolina university'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose school record fuzzily matches to coastal carolina university .', 'tostr': 'filter_eq { all_rows ; school ; coastal carolina university }'}, 'founded'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; school ; coastal carolina university } ; founded }', 'tointer': 'select the rows whose school record fuzzily matches to coastal carolina university . take the founded record of this row .'}], 'result': '-30', 'ind': 4, 'tostr': 'diff { hop { filter_eq { all_rows ; school ; high point university } ; founded } ; hop { filter_eq { all_rows ; school ; coastal carolina university } ; founded } }'}, '-30'], 'result': True, 'ind': 5, 'tostr': 'eq { diff { hop { filter_eq { all_rows ; school ; high point university } ; founded } ; hop { filter_eq { all_rows ; school ; coastal carolina university } ; founded } } ; -30 } = true', 'tointer': 'select the rows whose school record fuzzily matches to high point university . take the founded record of this row . select the rows whose school record fuzzily matches to coastal carolina university . take the founded record of this row . the second record is 30 larger than the first record .'}

eq { diff { hop { filter_eq { all_rows ; school ; high point university } ; founded } ; hop { filter_eq { all_rows ; school ; coastal carolina university } ; founded } } ; -30 } = true

select the rows whose school record fuzzily matches to high point university . take the founded record of this row . select the rows whose school record fuzzily matches to coastal carolina university . take the founded record of this row . the second record is 30 larger than the first 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, 'school_8': 8, 'high point university_9': 9, 'founded_10': 10, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_11': 11, 'school_12': 12, 'coastal carolina university_13': 13, 'founded_14': 14, '-30_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', 'school_8': 'school', 'high point university_9': 'high point university', 'founded_10': 'founded', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_11': 'all_rows', 'school_12': 'school', 'coastal carolina university_13': 'coastal carolina university', 'founded_14': 'founded', '-30_15': '-30'}

{'eq_5': [6], 'result_6': [], 'diff_4': [5], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_7': [0], 'school_8': [0], 'high point university_9': [0], 'founded_10': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_11': [1], 'school_12': [1], 'coastal carolina university_13': [1], 'founded_14': [3], '-30_15': [5]}

['school', 'location', 'founded', 'affiliation', 'nickname']

[['appalachian state university', 'boone , nc', '1899', 'public ( university of north carolina system )', 'mountaineers'], ['coastal carolina university', 'conway , sc', '1954', 'public', 'chanticleers'], ['high point university', 'high point , nc', '1924', 'private / methodist', 'panthers'], ['johnson & wales university', 'charlotte , nc', '2004', 'private / non - profit', 'wildcats'], ['virginia military institute', 'lexington , va', '1839', 'public military college', 'keydets']]

1991 foster 's cup

https://en.wikipedia.org/wiki/1991_Foster%27s_Cup

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16387700-1.html.csv

superlative

carlton had the highest score of any home team at the 1991 foster 's cup .

{'scope': 'all', 'col_superlative': '2', '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', 'home team score'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; home team score }'}, 'home team'], 'result': 'carlton', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; home team score } ; home team }'}, 'carlton'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; home team score } ; home team } ; carlton } = true', 'tointer': 'select the row whose home team score record of all rows is maximum . the home team record of this row is carlton .'}

eq { hop { argmax { all_rows ; home team score } ; home team } ; carlton } = true

select the row whose home team score record of all rows is maximum . the home team record of this row is carlton .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'home team score_5': 5, 'home team_6': 6, 'carlton_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'home team score_5': 'home team score', 'home team_6': 'home team', 'carlton_7': 'carlton'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'home team score_5': [0], 'home team_6': [1], 'carlton_7': [2]}

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

[['carlton', '27.9 ( 171 )', 'fitzroy', '13.8 ( 86 )', 'north hobart oval', '10100', 'sunday 3 february'], ['footscray', '9.6 ( 60 )', 'hawthorn', '19.25 ( 139 )', 'waverley park', '13196', 'wednesday 6 february'], ['collingwood', '11.17 ( 83 )', 'brisbane', '20.20 ( 140 )', 'gabba', '12461', 'saturday 10 february'], ['geelong', '11.13 ( 79 )', 'adelaide', '23.18 ( 156 )', 'football park', '20069', 'wednesday 13 february'], ['st kilda', '12.10 ( 82 )', 'west coast', '9.11 ( 65 )', 'waverley park', '13625', 'saturday 16 february'], ['melbourne', '15.13 ( 103 )', 'richmond', '12.10 ( 82 )', 'waverley park', '14993', 'wednesday 20 february'], ['north melbourne', '19.20 ( 134 )', 'sydney', '13.17 ( 95 )', 'bruce stadium', '5120', 'sunday 24 february']]

colonia ( a camp album )

https://en.wikipedia.org/wiki/Colonia_%28A_Camp_album%29

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18908421-5.html.csv

count

colonia ( a camp album ) has reveal records as its label 3 times .

{'scope': 'all', 'criterion': 'equal', 'value': 'reveal records', 'result': '3', 'col': '3', 'subset': None}

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

eq { count { filter_eq { all_rows ; label ; reveal records } } ; 3 } = true

select the rows whose label record fuzzily matches to reveal records . 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, 'label_5': 5, 'reveal records_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', 'label_5': 'label', 'reveal records_6': 'reveal records', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], 'label_5': [0], 'reveal records_6': [0], '3_7': [2]}

['region', 'date', 'label', 'format', 'catalog']

[['scandinavia', '28 january 2009', 'universal', 'cd', '0 - 6025 - 17918 - 7 - 7'], ['ireland', '30 january 2009', 'reveal records', 'cd / lp', 'reveal50cd / lp'], ['united kingdom', '2 february 2009', 'reveal records', 'cd / lp', 'reveal50cd / lp'], ['mainland europe', '20 march 2009', 'reveal records', 'cd / lp', 'reveal50cd / lp'], ['united states', 'april 28 , 2009', 'nettwerk', 'cd', '0 - 6700 - 30838 - 2 - 9']]

tasmania cricket team first - class records

https://en.wikipedia.org/wiki/Tasmania_cricket_team_first-class_records

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14412861-4.html.csv

comparative

tasmania scored more runs against queensland than they did against victoria .

{'row_1': '5', 'row_2': '1', 'col': '2', 'col_other': '3', 'relation': 'greater', 'record_mentioned': 'no', 'diff_result': None}

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

greater { hop { filter_eq { all_rows ; opponent ; queensland } ; runs } ; hop { filter_eq { all_rows ; opponent ; victoria } ; runs } } = true

select the rows whose opponent record fuzzily matches to queensland . take the runs record of this row . select the rows whose opponent record fuzzily matches to victoria . take the runs 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, 'opponent_7': 7, 'queensland_8': 8, 'runs_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'opponent_11': 11, 'victoria_12': 12, 'runs_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', 'opponent_7': 'opponent', 'queensland_8': 'queensland', 'runs_9': 'runs', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'opponent_11': 'opponent', 'victoria_12': 'victoria', 'runs_13': 'runs'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'opponent_7': [0], 'queensland_8': [0], 'runs_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'opponent_11': [1], 'victoria_12': [1], 'runs_13': [3]}

['rank', 'runs', 'opponent', 'venue', 'season']

[['1', '50', 'victoria', 'launceston cricket club ground , launceston', '1853 / 54'], ['2', '53', 'new south wales', 'bellerive oval , hobart', '2006 / 07'], ['3', '55', 'south australia', 'bellerive oval , hobart', '2010 / 11'], ['4', '57', 'victoria', 'launceston cricket club ground , launceston', '1850 / 51'], ['5', '62', 'queensland', 'gabba , brisbane', '2008 / 09']]

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

superlative

ferhat akdeniz is the tallest player on the galatasaray s.k. men 's volleyball team .

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

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

eq { hop { argmax { all_rows ; height } ; player } ; ferhat akdeniz } = true

select the row whose height record of all rows is maximum . the player record of this row is ferhat akdeniz .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'height_5': 5, 'player_6': 6, 'ferhat akdeniz_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'height_5': 'height', 'player_6': 'player', 'ferhat akdeniz_7': 'ferhat akdeniz'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'height_5': [0], 'player_6': [1], 'ferhat akdeniz_7': [2]}

['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']]

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

comparative

game 4 had drawn a larger crowd than game 1 drew .

{'row_1': '4', 'row_2': '1', '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', 'game', '4'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose game record fuzzily matches to 4 .', 'tostr': 'filter_eq { all_rows ; game ; 4 }'}, 'attendance'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; game ; 4 } ; attendance }', 'tointer': 'select the rows whose game record fuzzily matches to 4 . take the attendance record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'game', '1'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose game record fuzzily matches to 1 .', 'tostr': 'filter_eq { all_rows ; game ; 1 }'}, 'attendance'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; game ; 1 } ; attendance }', 'tointer': 'select the rows whose game record fuzzily matches to 1 . take the attendance record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; game ; 4 } ; attendance } ; hop { filter_eq { all_rows ; game ; 1 } ; attendance } } = true', 'tointer': 'select the rows whose game record fuzzily matches to 4 . take the attendance record of this row . select the rows whose game record fuzzily matches to 1 . take the attendance record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; game ; 4 } ; attendance } ; hop { filter_eq { all_rows ; game ; 1 } ; attendance } } = true

select the rows whose game record fuzzily matches to 4 . take the attendance record of this row . select the rows whose game record fuzzily matches to 1 . take the attendance 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, 'game_7': 7, '4_8': 8, 'attendance_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'game_11': 11, '1_12': 12, 'attendance_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', 'game_7': 'game', '4_8': '4', 'attendance_9': 'attendance', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'game_11': 'game', '1_12': '1', 'attendance_13': 'attendance'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'game_7': [0], '4_8': [0], 'attendance_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'game_11': [1], '1_12': [1], 'attendance_13': [3]}

['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']]

1968 vfl season

https://en.wikipedia.org/wiki/1968_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10808933-3.html.csv

ordinal

mcg venue recorded the highest crowd participation during the 1968 vfl season .

{'row': '2', 'col': '6', 'order': '1', 'col_other': '5', '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', 'crowd', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; crowd ; 1 }'}, 'venue'], 'result': 'mcg', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; crowd ; 1 } ; venue }'}, 'mcg'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true', 'tointer': 'select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg .'}

eq { hop { nth_argmax { all_rows ; crowd ; 1 } ; venue } ; mcg } = true

select the row whose crowd record of all rows is 1st maximum . the venue record of this row is mcg .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'crowd_5': 5, '1_6': 6, 'venue_7': 7, 'mcg_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', 'crowd_5': 'crowd', '1_6': '1', 'venue_7': 'venue', 'mcg_8': 'mcg'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'crowd_5': [0], '1_6': [0], 'venue_7': [1], 'mcg_8': [2]}

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

[['carlton', '1.11 ( 17 )', 'essendon', '7.8 ( 50 )', 'princes park', '37406', '25 april 1968'], ['richmond', '10.15 ( 75 )', 'geelong', '17.21 ( 123 )', 'mcg', '52175', '25 april 1968'], ['footscray', '14.10 ( 94 )', 'hawthorn', '16.9 ( 105 )', 'western oval', '14054', '27 april 1968'], ['collingwood', '2.19 ( 31 )', 'st kilda', '10.7 ( 67 )', 'victoria park', '29491', '27 april 1968'], ['south melbourne', '13.10 ( 88 )', 'melbourne', '14.14 ( 98 )', 'lake oval', '17260', '27 april 1968'], ['north melbourne', '15.17 ( 107 )', 'fitzroy', '14.7 ( 91 )', 'arden street oval', '13122', '27 april 1968']]

credit union challenge

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15315816-1.html.csv

count

three winners had the same prize of 8400 during the credit union golf challenge .

{'scope': 'all', 'criterion': 'equal', 'value': '8400', 'result': '3', 'col': '8', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', "winner 's share", '8400'], 'result': None, 'ind': 0, 'tointer': "select the rows whose winner 's share record is equal to 8400 .", 'tostr': "filter_eq { all_rows ; winner 's share ; 8400 }"}], 'result': '3', 'ind': 1, 'tostr': "count { filter_eq { all_rows ; winner 's share ; 8400 } }", 'tointer': "select the rows whose winner 's share record is equal to 8400 . the number of such rows is 3 ."}, '3'], 'result': True, 'ind': 2, 'tostr': "eq { count { filter_eq { all_rows ; winner 's share ; 8400 } } ; 3 } = true", 'tointer': "select the rows whose winner 's share record is equal to 8400 . the number of such rows is 3 ."}

eq { count { filter_eq { all_rows ; winner 's share ; 8400 } } ; 3 } = true

select the rows whose winner 's share record is equal to 8400 . the number of such rows is 3 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_eq_0': 0, 'all_rows_4': 4, "winner 's share_5": 5, '8400_6': 6, '3_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', "winner 's share_5": "winner 's share", '8400_6': '8400', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], "winner 's share_5": [0], '8400_6': [0], '3_7': [2]}

['year', 'dates', 'champion', 'country', 'score', 'tournament location', 'purse', "winner 's share"]

[['2013', 'jul 12 - 14', 'wei - ling hsu', 'taiwan', '202 ( - 11 )', 'capital hills at albany', '100000', '15000'], ['2012', 'aug 3 - 5', 'jaclyn sweeney', 'united states', '203 ( - 10 )', 'capital hills at albany', '100000', '15000'], ['2011', 'sep 9 - 11', 'sydnee michaels', 'united states', '202 ( - 8 )', 'capital hills at albany', '120000', '16800'], ['2010', 'sep 3 - 5', 'cindy lacrosse', 'united states', '208 ( - 5 )', 'capital hills at albany', '120000', '16800'], ['2009', 'sep 4 - 6', 'song yi choi', 'south korea', '205 ( - 8 )', 'capital hills at albany', '110000', '15400'], ['2008', 'sep 5 - 7', 'sarah - jane kenyon', 'australia', '204 ( - 9 )', 'capital hills at albany', '100000', '14000'], ['2007', 'sep 7 - 9', 'onnarin sattayabanphot', 'thailand', '210 ( - 3 )', 'capital hills at albany', '100000', '14000'], ['2006', 'sep 8 - 10', 'ji min jeong', 'south korea', '206 ( - 7 )', 'capital hills at albany', '85000', '11900'], ['2005', 'jul 15 - 17', 'seon - hwa lee', 'south korea', '199 ( - 14 )', 'capital hills at albany', '70000', '9800'], ['2004', 'aug 13 - 15', 'nicole perrot', 'paraguay', '203 ( - 10 )', 'capital hills at albany', '70000', '9800'], ['2003', 'jul 17 - 20', 'lindsey wright', 'australia', '205 ( - 8 )', 'orchard creek golf club', '60000', '8400'], ['2002', 'jul 5 - 7', 'mariam nagl', 'brazil', '210 ( - 3 )', 'orchard creek golf club', '60000', '8400'], ['2001', 'jul 6 - 8', 'angela buzminski', 'canada', '208 ( - 8 )', 'western turnpike golf course', '60000', '8400'], ['2000', 'jul 7 - 9', 'dodie mazzuca', 'united states', '218 ( + 2 )', 'western turnpike golf course', '50000', '7000']]

list of rugby league stadiums by capacity

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18735456-2.html.csv

superlative

of the rugby league stadiums , the one with the largest capacity is anz stadium .

{'scope': 'all', 'col_superlative': '2', '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', 'capacity'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; capacity }'}, 'stadium'], 'result': 'anz stadium', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; capacity } ; stadium }'}, 'anz stadium'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; capacity } ; stadium } ; anz stadium } = true', 'tointer': 'select the row whose capacity record of all rows is maximum . the stadium record of this row is anz stadium .'}

eq { hop { argmax { all_rows ; capacity } ; stadium } ; anz stadium } = true

select the row whose capacity record of all rows is maximum . the stadium record of this row is anz stadium .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'capacity_5': 5, 'stadium_6': 6, 'anz stadium_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'capacity_5': 'capacity', 'stadium_6': 'stadium', 'anz stadium_7': 'anz stadium'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'capacity_5': [0], 'stadium_6': [1], 'anz stadium_7': [2]}

['stadium', 'capacity', 'city', 'country', 'home team / s', 'closed ( as a rl stadium )']

[['anz stadium', '59000', 'brisbane', 'australia', 'brisbane broncos', '2003'], ['sydney sports ground', '35000', 'sydney', 'australia', 'eastern suburbs', '1986'], ['redfern oval', '23000', 'sydney', 'australia', 'south sydney', '1987'], ['stade sébastien charléty', '20000', 'paris', 'france', 'paris saint - germain', '1997'], ['olympic park stadium', '18500', 'melbourne', 'australia', 'melbourne storm', '2009'], ['knowsley road', '17500', 'st helens', 'england', 'st helens rlfc', '2010'], ['the willows', '11363', 'salford', 'england', 'salford city reds', '2011'], ['the boulevard', '10500', 'kingston upon hull', 'england', 'hull', '2000'], ['barnet copthall', '5000', 'london', 'england', 'london crusaders', '1994']]

norwegian international

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12121208-1.html.csv

count

julienne schenk participated in the women 's singles a three times .

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

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

eq { count { filter_eq { all_rows ; women 's singles ; juliane schenk } } ; 3 } = true

select the rows whose women 's singles record fuzzily matches to juliane schenk . 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, "women 's singles_5": 5, 'juliane schenk_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', "women 's singles_5": "women 's singles", 'juliane schenk_6': 'juliane schenk', '3_7': '3'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_str_eq_0': [1], 'all_rows_4': [0], "women 's singles_5": [0], 'juliane schenk_6': [0], '3_7': [2]}

['year', "men 's singles", "women 's singles", "men 's doubles", "women 's doubles", 'mixed doubles']

[['2012', 'chou tien - chen', 'sashina vignes waran', 'ruud bosch koen ridder', 'samantha barning eefje muskens', 'jorrit de ruiter samantha barning'], ['2011', 'ville lang', 'linda zechiri', 'rasmus bonde anders kristiansen', 'eva lee paula lynn obanana', 'sam magee chloe magee'], ['2010', 'hans - kristian vittinghus', 'olga konon', 'ingo kindervater johannes schoettler', 'lotte jonathans paulien van dooremalen', 'michael fuchs birgit overzier'], ['2009', 'hans - kristian vittinghus', 'juliane schenk', 'rasmus bonde simon mollyhus', 'helle nielsen marie røpke', 'marcus ellis heather olver'], ['2008', 'ville lang', 'zhang xi', 'michael fuchs ingo kindervater', 'anastasia russkikh irina hlebko', 'michael fuchs annekatrin lillie'], ['2007', 'marc zwiebler', 'juliane schenk', 'howard bach bob malaythong', 'anastasia russkikh ekaterina ananina', 'kristof hopp birgit overzier'], ['2006', 'hans - kristian vittinghus', 'sara persson', 'anton nazarenko andrey ashmarin', 'imogen bankier emma mason', 'imam sodikin irawan elin bergblom'], ['2005', 'eric pang', 'juliane schenk', 'vidre wilbowo imam sodikin irawan', 'nicole grether juliane schenk', 'kristof hopp birgit overzier'], ['2004', 'björn joppien', 'petra overzier', 'kristof hopp ingo kindervater', 'liza parker suzanne rayappan', 'frederik bergström johanna persson'], ['2003', 'per - henrik croona', 'tine rasmussen', 'lee jae - jin hwang ji - man', 'ha jung - eun oh seul - ki', 'lee jae - jin lee eun - woo'], ['2002', 'kasperi salo', 'tine rasmussen', 'alexandr nikolaenko nikolaj nikolaenko', 'frida andreasson lina uhac', 'jörgen olsson frida andreasson'], ['2001', 'irwansyah', 'anu weckstrom', 'martin delfs jonas glyager jensen', 'karina sorensen julie houmann', 'tommy sorensen karina sorensen']]

1960 vfl season

https://en.wikipedia.org/wiki/1960_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10775890-6.html.csv

aggregation

the average away team score achieved was 8.75 on the 28th of may 1960 .

{'scope': 'all', 'col': '4', 'type': 'average', 'result': '8.75', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'avg', 'args': ['all_rows', 'away team score'], 'result': '8.75', 'ind': 0, 'tostr': 'avg { all_rows ; away team score }'}, '8.75'], 'result': True, 'ind': 1, 'tostr': 'round_eq { avg { all_rows ; away team score } ; 8.75 } = true', 'tointer': 'the average of the away team score record of all rows is 8.75 .'}

round_eq { avg { all_rows ; away team score } ; 8.75 } = true

the average of the away team score record of all rows is 8.75 .

2

2

{'eq_1': 1, 'result_2': 2, 'avg_0': 0, 'all_rows_3': 3, 'away team score_4': 4, '8.75_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'avg_0': 'avg', 'all_rows_3': 'all_rows', 'away team score_4': 'away team score', '8.75_5': '8.75'}

{'eq_1': [2], 'result_2': [], 'avg_0': [1], 'all_rows_3': [0], 'away team score_4': [0], '8.75_5': [1]}

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

[['melbourne', '17.22 ( 124 )', 'richmond', '4.8 ( 32 )', 'mcg', '27249', '28 may 1960'], ['footscray', '6.11 ( 47 )', 'st kilda', '10.5 ( 65 )', 'western oval', '22126', '28 may 1960'], ['north melbourne', '7.6 ( 48 )', 'hawthorn', '9.8 ( 62 )', 'arden street oval', '8600', '28 may 1960'], ['fitzroy', '8.7 ( 55 )', 'essendon', '6.14 ( 50 )', 'brunswick street oval', '25632', '28 may 1960'], ['south melbourne', '12.8 ( 80 )', 'collingwood', '11.12 ( 78 )', 'lake oval', '27000', '28 may 1960'], ['geelong', '17.17 ( 119 )', 'carlton', '10.14 ( 74 )', 'kardinia park', '16589', '28 may 1960']]

2009 - 10 alabama crimson tide men 's basketball team

https://en.wikipedia.org/wiki/2009%E2%80%9310_Alabama_Crimson_Tide_men%27s_basketball_team

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-25360865-1.html.csv

comparative

on the 2009-2010 alabama crimson tide men 's basketball team , justin knox was the same height as jamychal green .

{'row_1': '11', 'row_2': '10', 'col': '4', 'col_other': '2', 'relation': 'equal', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'justin knox'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose name record fuzzily matches to justin knox .', 'tostr': 'filter_eq { all_rows ; name ; justin knox }'}, 'height'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; name ; justin knox } ; height }', 'tointer': 'select the rows whose name record fuzzily matches to justin knox . take the height record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'name', 'jamychal green'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose name record fuzzily matches to jamychal green .', 'tostr': 'filter_eq { all_rows ; name ; jamychal green }'}, 'height'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; name ; jamychal green } ; height }', 'tointer': 'select the rows whose name record fuzzily matches to jamychal green . take the height record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'eq { hop { filter_eq { all_rows ; name ; justin knox } ; height } ; hop { filter_eq { all_rows ; name ; jamychal green } ; height } } = true', 'tointer': 'select the rows whose name record fuzzily matches to justin knox . take the height record of this row . select the rows whose name record fuzzily matches to jamychal green . take the height record of this row . the first record fuzzily matches to the second record .'}

eq { hop { filter_eq { all_rows ; name ; justin knox } ; height } ; hop { filter_eq { all_rows ; name ; jamychal green } ; height } } = true

select the rows whose name record fuzzily matches to justin knox . take the height record of this row . select the rows whose name record fuzzily matches to jamychal green . take the height record of this row . the first record fuzzily matches to the second record .

5

5

{'str_eq_4': 4, 'result_5': 5, 'str_hop_2': 2, 'filter_str_eq_0': 0, 'all_rows_6': 6, 'name_7': 7, 'justin knox_8': 8, 'height_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'name_11': 11, 'jamychal green_12': 12, 'height_13': 13}

{'str_eq_4': 'str_eq', 'result_5': 'true', 'str_hop_2': 'str_hop', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_6': 'all_rows', 'name_7': 'name', 'justin knox_8': 'justin knox', 'height_9': 'height', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'name_11': 'name', 'jamychal green_12': 'jamychal green', 'height_13': 'height'}

{'str_eq_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'name_7': [0], 'justin knox_8': [0], 'height_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'name_11': [1], 'jamychal green_12': [1], 'height_13': [3]}

['', 'name', 'position', 'height', 'weight', 'year', 'home town', 'last school']

[['1', 'anthony brock', 'guard', '5 - 9', '165', 'senior', 'little rock , ark', 'itawamba cc'], ['2', 'mikhail torrance', 'guard', '6 - 5', '210', 'senior', 'eight mile , ala', 'mary montgomery hs'], ['5', 'tony mitchell', 'forward', '6 - 6', '185', 'freshman', 'swainsboro , ga', 'central park christian hs'], ['10', 'ben eblen', 'guard', '6 - 1', '180', 'freshman', 'isle of palms , sc', 'florida air academy'], ['20', 'greg cage', 'guard', '6 - 4', '212', 'senior', 'indianapolis , ind', 'bishop chatard hs'], ['21', 'senario hillman', 'guard', '6 - 1', '192', 'junior', 'irwinton , ga', 'wilkinson county hs'], ['23', 'demetrius jemison', 'forward', '6 - 8', '240', 'senior', 'birmingham , ala', 'huffman hs'], ['24', 'charvez davis', 'guard', '6 - 3', '190', 'junior', 'montgomery , ala', 'northwest florida state college'], ['25', 'andrew steele', 'guard', '6 - 3', '215', 'sophomore', 'birmingham , ala', 'john carroll hs'], ['32', 'jamychal green', 'forward', '6 - 9', '220', 'sophomore', 'montgomery , ala', 'st jude hs'], ['40', 'justin knox', 'forward', '6 - 9', '240', 'junior', 'tuscaloosa , ala', 'central hs']]

list of the tudors episodes

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-10413597-5.html.csv

majority

all of the episodes of the tudors were written by michael hirst .

{'scope': 'all', 'col': '6', 'most_or_all': 'all', 'criterion': 'equal', 'value': 'michael hirst', 'subset': None}

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

all_eq { all_rows ; written by ; michael hirst } = true

for the written by records of all rows , all of them fuzzily match to michael hirst .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'written by_3': 3, 'michael hirst_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'written by_3': 'written by', 'michael hirst_4': 'michael hirst'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'written by_3': [0], 'michael hirst_4': [0]}

['no in series', 'no in season', 'title', 'setting', 'directed by', 'written by', 'us viewers ( million )', 'original air date']

[['29', '1', 'moment of nostalgia', 'summer 1540', 'dearbhla walsh', 'michael hirst', '0.88', 'april 11 , 2010'], ['30', '2', 'sister', 'winter 1540', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 18 , 2010'], ['31', '3', 'something for you', 'spring 1541', 'dearbhla walsh', 'michael hirst', 'n / a', 'april 25 , 2010'], ['32', '4', 'natural ally', 'summer / autumn 1541', 'ciarán donnelly', 'michael hirst', '0.90', 'may 2 , 2010'], ['33', '5', 'bottom of the pot', 'winter 1541 / february 13 , 1542', 'ciarán donnelly', 'michael hirst', '0.93', 'may 9 , 2010'], ['34', '6', 'you have my permission', '1542', 'ciarán donnelly', 'michael hirst', 'n / a', 'may 16 , 2010'], ['35', '7', 'sixth and the final wife', '1543', 'jeremy podeswa', 'michael hirst', '0.95', 'may 23 , 2010'], ['36', '8', 'as it should be', '1544', 'jeremy podeswa', 'michael hirst', '0.99', 'june 6 , 2010'], ['37', '9', 'secrets of the heart', '1544 - 1546', 'ciarán donnelly', 'michael hirst', '0.72', 'june 13 , 2010']]

rowing at the 2008 summer olympics - women 's single sculls

https://en.wikipedia.org/wiki/Rowing_at_the_2008_Summer_Olympics_%E2%80%93_Women%27s_single_sculls

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18662695-9.html.csv

comparative

mayra gonzález had a faster time than camila vargas in the 2008 summer olympics - women 's single sculls .

{'row_1': '4', 'row_2': '5', 'col': '4', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

{'func': 'less', 'args': [{'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'mayra gonzález'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose athlete record fuzzily matches to mayra gonzález .', 'tostr': 'filter_eq { all_rows ; athlete ; mayra gonzález }'}, 'time'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; athlete ; mayra gonzález } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to mayra gonzález . take the time record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'athlete', 'camila vargas'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose athlete record fuzzily matches to camila vargas .', 'tostr': 'filter_eq { all_rows ; athlete ; camila vargas }'}, 'time'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; athlete ; camila vargas } ; time }', 'tointer': 'select the rows whose athlete record fuzzily matches to camila vargas . take the time record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'less { hop { filter_eq { all_rows ; athlete ; mayra gonzález } ; time } ; hop { filter_eq { all_rows ; athlete ; camila vargas } ; time } } = true', 'tointer': 'select the rows whose athlete record fuzzily matches to mayra gonzález . take the time record of this row . select the rows whose athlete record fuzzily matches to camila vargas . take the time record of this row . the first record is less than the second record .'}

less { hop { filter_eq { all_rows ; athlete ; mayra gonzález } ; time } ; hop { filter_eq { all_rows ; athlete ; camila vargas } ; time } } = true

select the rows whose athlete record fuzzily matches to mayra gonzález . take the time record of this row . select the rows whose athlete record fuzzily matches to camila vargas . take the time 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, 'athlete_7': 7, 'mayra gonzález_8': 8, 'time_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'athlete_11': 11, 'camila vargas_12': 12, 'time_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', 'athlete_7': 'athlete', 'mayra gonzález_8': 'mayra gonzález', 'time_9': 'time', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'athlete_11': 'athlete', 'camila vargas_12': 'camila vargas', 'time_13': 'time'}

{'less_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'athlete_7': [0], 'mayra gonzález_8': [0], 'time_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'athlete_11': [1], 'camila vargas_12': [1], 'time_13': [3]}

['rank', 'athlete', 'country', 'time', 'notes']

[['1', 'miroslava knapková', 'czech republic', '7:30.33', 'sa / b'], ['2', 'sophie balmary', 'france', '7:37.01', 'sa / b'], ['3', 'iva obradović', 'serbia', '7:39.16', 'sa / b'], ['4', 'mayra gonzález', 'cuba', '7:45.75', 'sc / d'], ['5', 'camila vargas', 'el salvador', '8:11.79', 'sc / d'], ['6', 'latt shwe zin', 'myanmar', '8:17.76', 'sc / d']]

1951 in brazilian football

https://en.wikipedia.org/wiki/1951_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15303773-1.html.csv

comparative

in 1951 brazilian football , palmeiras had fewer goals scored against them than flamengo .

{'row_1': '1', 'row_2': '4', 'col': '7', 'col_other': '2', 'relation': 'less', 'record_mentioned': 'no', 'diff_result': None}

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

less { hop { filter_eq { all_rows ; team ; palmeiras } ; against } ; hop { filter_eq { all_rows ; team ; flamengo } ; against } } = true

select the rows whose team record fuzzily matches to palmeiras . take the against record of this row . select the rows whose team record fuzzily matches to flamengo . take the against 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, 'team_7': 7, 'palmeiras_8': 8, 'against_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'team_11': 11, 'flamengo_12': 12, 'against_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', 'team_7': 'team', 'palmeiras_8': 'palmeiras', 'against_9': 'against', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'team_11': 'team', 'flamengo_12': 'flamengo', 'against_13': 'against'}

{'less_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'team_7': [0], 'palmeiras_8': [0], 'against_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'team_11': [1], 'flamengo_12': [1], 'against_13': [3]}

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

[['1', 'palmeiras', '10', '7', '0', '2', '14', '11'], ['2', 'corinthians', '10', '7', '2', '1', '12', '8'], ['3', 'bangu', '7', '7', '1', '3', '18', '4'], ['4', 'flamengo', '7', '7', '1', '3', '19', '- 4'], ['5', 'américa', '7', '7', '3', '2', '19', '0'], ['6', 'portuguesa', '7', '7', '1', '3', '23', '- 6'], ['7', 'vasco da gama', '6', '7', '4', '2', '18', '- 3'], ['8', 'são paulo', '2', '7', '2', '5', '18', '- 10']]

1974 vfl season

https://en.wikipedia.org/wiki/1974_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10869646-17.html.csv

majority

in the games of 1974 vfl season listed the majority of crowds were over 15000 .

{'scope': 'all', 'col': '6', 'most_or_all': 'most', 'criterion': 'greater_than', 'value': '15000', 'subset': None}

{'func': 'most_greater', 'args': ['all_rows', 'crowd', '15000'], 'result': True, 'ind': 0, 'tointer': 'for the crowd records of all rows , most of them are greater than 15000 .', 'tostr': 'most_greater { all_rows ; crowd ; 15000 } = true'}

most_greater { all_rows ; crowd ; 15000 } = true

for the crowd records of all rows , most of them are greater than 15000 .

1

1

{'most_greater_0': 0, 'result_1': 1, 'all_rows_2': 2, 'crowd_3': 3, '15000_4': 4}

{'most_greater_0': 'most_greater', 'result_1': 'true', 'all_rows_2': 'all_rows', 'crowd_3': 'crowd', '15000_4': '15000'}

{'most_greater_0': [1], 'result_1': [], 'all_rows_2': [0], 'crowd_3': [0], '15000_4': [0]}

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

[['essendon', '9.10 ( 64 )', 'footscray', '13.15 ( 93 )', 'windy hill', '16250', '27 july 1974'], ['st kilda', '10.13 ( 73 )', 'north melbourne', '11.16 ( 82 )', 'moorabbin oval', '15954', '27 july 1974'], ['hawthorn', '13.28 ( 106 )', 'fitzroy', '8.10 ( 58 )', 'princes park', '6198', '27 july 1974'], ['melbourne', '15.21 ( 111 )', 'collingwood', '17.13 ( 115 )', 'mcg', '22893', '27 july 1974'], ['south melbourne', '14.17 ( 101 )', 'carlton', '11.14 ( 80 )', 'lake oval', '14114', '27 july 1974'], ['richmond', '13.15 ( 93 )', 'geelong', '8.9 ( 57 )', 'vfl park', '15578', '27 july 1974']]

list of animals of farthing wood characters

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11206371-1.html.csv

comparative

the rabbits appeared in more seasons of farthing wood than the mole did .

{'row_1': '10', 'row_2': '8', 'col': '6', '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', 'animal name', 'the rabbits'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose animal name record fuzzily matches to the rabbits .', 'tostr': 'filter_eq { all_rows ; animal name ; the rabbits }'}, 'tv seasons'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons }', 'tointer': 'select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row .'}, {'func': 'str_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'animal name', 'mole'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose animal name record fuzzily matches to mole .', 'tostr': 'filter_eq { all_rows ; animal name ; mole }'}, 'tv seasons'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons }', 'tointer': 'select the rows whose animal name record fuzzily matches to mole . take the tv seasons record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons } ; hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons } } = true', 'tointer': 'select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row . select the rows whose animal name record fuzzily matches to mole . take the tv seasons record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; animal name ; the rabbits } ; tv seasons } ; hop { filter_eq { all_rows ; animal name ; mole } ; tv seasons } } = true

select the rows whose animal name record fuzzily matches to the rabbits . take the tv seasons record of this row . select the rows whose animal name record fuzzily matches to mole . take the tv seasons 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, 'animal name_7': 7, 'the rabbits_8': 8, 'tv seasons_9': 9, 'str_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'animal name_11': 11, 'mole_12': 12, 'tv seasons_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', 'animal name_7': 'animal name', 'the rabbits_8': 'the rabbits', 'tv seasons_9': 'tv seasons', 'str_hop_3': 'str_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'animal name_11': 'animal name', 'mole_12': 'mole', 'tv seasons_13': 'tv seasons'}

{'greater_4': [5], 'result_5': [], 'str_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'animal name_7': [0], 'the rabbits_8': [0], 'tv seasons_9': [2], 'str_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'animal name_11': [1], 'mole_12': [1], 'tv seasons_13': [3]}

['animal name', 'species', 'books', 'tv series', 'gender', 'tv seasons']

[['fox', 'fox', 'yes', 'yes', 'male', '1 , 2 , 3'], ['badger', 'badger', 'yes', 'yes', 'male', '1 , 2'], ['toad', 'toad', 'yes', 'yes', 'male', '1 , 2 , 3'], ['owl', 'owl', 'yes ( as tawny owl )', 'yes', 'female ( tv ) male ( books )', '1 , 2 , 3'], ['weasel', 'weasel', 'yes', 'yes', 'female ( tv ) male ( books )', '1 , 2 , 3'], ['adder', 'snake', 'yes', 'yes', 'female ( tv ) male ( books )', '1 , 2 , 3'], ['kestrel', 'kestrel', 'yes', 'yes', 'female ( tv ) male ( books )', '1 , 2'], ['mole', 'mole', 'yes', 'yes', 'male', '1 , 2'], ['the pheasants', 'pheasants', 'yes', 'yes', 'both', '1'], ['the rabbits', 'rabbits', 'yes', 'yes', 'both', '1 , 2 , 3'], ['the hares', 'hares', 'yes', 'yes', 'both', '1 , 2'], ['the hedgehogs', 's hedgehog', 'yes', 'yes', 'both', '1'], ['the squirrels', 'squirrels', 'yes', 'yes', 'both', '1 , 2 , 3'], ['the voles', 'voles', 'yes', 'yes', 'both', '1 , 2'], ['the shrews', 's shrew', 'no', 'yes', 'both', '1 , 2'], ['the fieldmice', 'field mice', 'yes', 'yes ( as the mice )', 'both', '1 , 2'], ['the lizards / the newts', 'lizards / newts', 'yes ( lizards )', 'yes ( newts )', 'both', '1']]

1963 in brazilian football

https://en.wikipedia.org/wiki/1963_in_Brazilian_football

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-15244400-2.html.csv

unique

of the teams in the top 5 of the 1963 brazilian football season , only one had more than 3 drawn games .

{'scope': 'subset', 'row': '4', 'col': '5', 'col_other': 'n/a', 'criterion': 'greater_than', 'value': '3', 'subset': {'col': '1', 'criterion': 'less_than_eq', 'value': '5'}}

{'func': 'only', 'args': [{'func': 'filter_greater', 'args': [{'func': 'filter_less_eq', 'args': ['all_rows', 'position', '5'], 'result': None, 'ind': 0, 'tostr': 'filter_less_eq { all_rows ; position ; 5 }', 'tointer': 'select the rows whose position record is less than or equal to 5 .'}, 'drawn', '3'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose position record is less than or equal to 5 . among these rows , select the rows whose drawn record is greater than 3 .', 'tostr': 'filter_greater { filter_less_eq { all_rows ; position ; 5 } ; drawn ; 3 }'}], 'result': True, 'ind': 2, 'tostr': 'only { filter_greater { filter_less_eq { all_rows ; position ; 5 } ; drawn ; 3 } } = true', 'tointer': 'select the rows whose position record is less than or equal to 5 . among these rows , select the rows whose drawn record is greater than 3 . there is only one such row in the table .'}

only { filter_greater { filter_less_eq { all_rows ; position ; 5 } ; drawn ; 3 } } = true

select the rows whose position record is less than or equal to 5 . among these rows , select the rows whose drawn record is greater than 3 . there is only one such row in the table .

3

3

{'only_2': 2, 'result_3': 3, 'filter_greater_1': 1, 'filter_less_eq_0': 0, 'all_rows_4': 4, 'position_5': 5, '5_6': 6, 'drawn_7': 7, '3_8': 8}

{'only_2': 'only', 'result_3': 'true', 'filter_greater_1': 'filter_greater', 'filter_less_eq_0': 'filter_less_eq', 'all_rows_4': 'all_rows', 'position_5': 'position', '5_6': '5', 'drawn_7': 'drawn', '3_8': '3'}

{'only_2': [3], 'result_3': [], 'filter_greater_1': [2], 'filter_less_eq_0': [1], 'all_rows_4': [0], 'position_5': [0], '5_6': [0], 'drawn_7': [1], '3_8': [1]}

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

[['1', 'santos', '13', '9', '1', '2', '15', '15'], ['2', 'corinthians', '12', '9', '0', '3', '9', '8'], ['3', 'fluminense', '11', '9', '3', '2', '12', '1'], ['4', 'botafogo', '10', '9', '4', '2', '14', '2'], ['5', 'palmeiras', '10', '9', '2', '3', '12', '0'], ['6', 'portuguesa', '9', '9', '3', '3', '21', '- 3'], ['7', 'portuguesa', '8', '9', '0', '5', '13', '1'], ['8', 'são paulo', '8', '9', '2', '4', '16', '- 5'], ['9', 'vasco da gama', '7', '9', '5', '3', '12', '- 3'], ['10', 'olaria', '7', '9', '2', '7', '23', '- 14']]

political appointments system in hong kong

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-17964087-1.html.csv

superlative

the oldest person to have been appointed to office in hong kong happened to have been a canadian .

{'scope': 'all', 'col_superlative': '3', 'row_superlative': '7', 'value_mentioned': 'no', 'max_or_min': 'max', 'other_col': '4', 'subset': None}

{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'argmax', 'args': ['all_rows', 'age at appointment'], 'result': None, 'ind': 0, 'tostr': 'argmax { all_rows ; age at appointment }'}, 'foreign nationality'], 'result': 'canadian', 'ind': 1, 'tostr': 'hop { argmax { all_rows ; age at appointment } ; foreign nationality }'}, 'canadian'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { argmax { all_rows ; age at appointment } ; foreign nationality } ; canadian } = true', 'tointer': 'select the row whose age at appointment record of all rows is maximum . the foreign nationality record of this row is canadian .'}

eq { hop { argmax { all_rows ; age at appointment } ; foreign nationality } ; canadian } = true

select the row whose age at appointment record of all rows is maximum . the foreign nationality record of this row is canadian .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmax_0': 0, 'all_rows_4': 4, 'age at appointment_5': 5, 'foreign nationality_6': 6, 'canadian_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmax_0': 'argmax', 'all_rows_4': 'all_rows', 'age at appointment_5': 'age at appointment', 'foreign nationality_6': 'foreign nationality', 'canadian_7': 'canadian'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmax_0': [1], 'all_rows_4': [0], 'age at appointment_5': [0], 'foreign nationality_6': [1], 'canadian_7': [2]}

['romanised name', 'chinese name', 'age at appointment', 'foreign nationality', 'portfolio attachment', 'govt salary']

[['chen wei - on , kenneth', '陳維安', '43', 'n / a', 'education', 'hk223585'], ['hui hiu - fai , florence', '許曉暉', '34', 'n / a', 'home affairs', 'hk223585'], ['leung fung - yee , julia', '梁鳳儀', '48', 'british', 'financial services and the treasury', 'hk223585'], ['leung , gabriel matthew', '梁卓偉', '35', 'canadian', 'food and health', 'hk208680'], ['poon kit , kitty', '潘潔', '45', 'us', 'environment', 'hk208680'], ['tam chi - yuen , raymond', '譚志源', '44', 'british', 'constitutional and mainland affairs', 'hk208680'], ['so kam - leung , gregory', '蘇錦樑', '49', 'canadian', 'commerce and economic development', 'hk223585'], ['yau shing - mu', '邱誠武', '48', 'n / a', 'transport and housing', 'hk 208680']]

2010 fedex cup playoffs

https://en.wikipedia.org/wiki/2010_FedEx_Cup_Playoffs

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-28498999-4.html.csv

unique

england is the only country with only 1 player in the top 9 in the 2010 fedex cup playoffs .

{'scope': 'all', 'row': '3', 'col': '3', 'col_other': 'n/a', 'criterion': 'equal', 'value': 'england', 'subset': None}

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

only { filter_eq { all_rows ; country ; england } } = true

select the rows whose country record fuzzily matches to england . 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, 'country_4': 4, 'england_5': 5}

{'only_1': 'only', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'country_4': 'country', 'england_5': 'england'}

{'only_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'country_4': [0], 'england_5': [0]}

['', 'player', 'country', 'score', 'to par', 'winnings', 'after', 'before']

[['1', 'charley hoffman', 'united states', '64 + 67 + 69 + 62 = 262', '- 22', '1350000', '2', '59'], ['t2', 'jason day', 'australia', '63 + 67 + 66 + 71 = 267', '- 17', '560000', '4', '14'], ['t2', 'luke donald', 'england', '65 + 67 + 66 + 69 = 267', '- 17', '560000', '5', '17'], ['t2', 'geoff ogilvy', 'australia', '64 + 72 + 65 + 66 = 267', '- 17', '560000', '9', '52'], ['t5', 'tom gillis', 'united states', '67 + 71 + 65 + 65 = 268', '- 16', '273750', '48', '92'], ['t5', 'adam scott', 'australia', '67 + 69 + 65 + 67 = 268', '- 16', '273750', '15', '19'], ['t5', 'brandt snedeker', 'united states', '66 + 64 + 67 + 71 = 268', '- 16', '273750', '31', '53'], ['8', 'john senden', 'australia', '66 + 68 + 69 + 67 = 270', '- 14', '232500', '38', '64'], ['9', 'steve stricker', 'united states', '65 + 68 + 67 + 71 = 271', '- 13', '217500', '3', '2']]

1941 vfl season

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10807673-16.html.csv

majority

all games of the 1941 vfl season were played on the 16th of august .

{'scope': 'all', 'col': '7', 'most_or_all': 'all', 'criterion': 'fuzzily_match', 'value': '16 august', 'subset': None}

{'func': 'all_str_eq', 'args': ['all_rows', 'date', '16 august'], 'result': True, 'ind': 0, 'tointer': 'for the date records of all rows , all of them fuzzily match to 16 august .', 'tostr': 'all_eq { all_rows ; date ; 16 august } = true'}

all_eq { all_rows ; date ; 16 august } = true

for the date records of all rows , all of them fuzzily match to 16 august .

1

1

{'all_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'date_3': 3, '16 august_4': 4}

{'all_str_eq_0': 'all_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'date_3': 'date', '16 august_4': '16 august'}

{'all_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'date_3': [0], '16 august_4': [0]}

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

[['fitzroy', '14.15 ( 99 )', 'richmond', '12.16 ( 88 )', 'brunswick street oval', '11000', '16 august 1941'], ['essendon', '19.17 ( 131 )', 'hawthorn', '14.9 ( 93 )', 'windy hill', '7000', '16 august 1941'], ['carlton', '20.17 ( 137 )', 'st kilda', '11.14 ( 80 )', 'princes park', '8000', '16 august 1941'], ['south melbourne', '10.10 ( 70 )', 'geelong', '10.9 ( 69 )', 'lake oval', '4000', '16 august 1941'], ['north melbourne', '15.14 ( 104 )', 'footscray', '11.22 ( 88 )', 'arden street oval', '8000', '16 august 1941'], ['melbourne', '17.8 ( 110 )', 'collingwood', '11.21 ( 87 )', 'mcg', '31000', '16 august 1941']]

rugby union at the 2002 asian games

https://en.wikipedia.org/wiki/Rugby_union_at_the_2002_Asian_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-14335046-1.html.csv

ordinal

during the rugby union at the 2002 asian games , japan ranked 3rd winning only 1 silver medal .

{'scope': 'all', 'row': '3', 'col': '1', 'order': '3', 'col_other': '2,4', 'max_or_min': 'min_to_max', 'value_mentioned': 'yes', 'subset': None}

{'func': 'and', 'args': [{'func': 'eq', 'args': [{'func': 'nth_min', 'args': ['all_rows', 'rank', '3'], 'result': '3', 'ind': 0, 'tostr': 'nth_min { all_rows ; rank ; 3 }', 'tointer': 'the 3rd minimum rank record of all rows is 3 .'}, '3'], 'result': True, 'ind': 1, 'tostr': 'eq { nth_min { all_rows ; rank ; 3 } ; 3 }', 'tointer': 'the 3rd minimum rank record of all rows is 3 .'}, {'func': 'and', 'args': [{'func': 'str_eq', 'args': [{'func': 'str_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; rank ; 3 }'}, 'nation'], 'result': 'japan ( jpn )', 'ind': 3, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 3 } ; nation }'}, 'japan ( jpn )'], 'result': True, 'ind': 4, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 3 } ; nation } ; japan ( jpn ) }', 'tointer': 'the nation record of the row with 3rd minimum rank record is japan ( jpn ) .'}, {'func': 'eq', 'args': [{'func': 'num_hop', 'args': [{'func': 'nth_argmin', 'args': ['all_rows', 'rank', '3'], 'result': None, 'ind': 2, 'tostr': 'nth_argmin { all_rows ; rank ; 3 }'}, 'silver'], 'result': '1', 'ind': 5, 'tostr': 'hop { nth_argmin { all_rows ; rank ; 3 } ; silver }'}, '1'], 'result': True, 'ind': 6, 'tostr': 'eq { hop { nth_argmin { all_rows ; rank ; 3 } ; silver } ; 1 }', 'tointer': 'the silver record of the row with 3rd minimum rank record is 1 .'}], 'result': True, 'ind': 7, 'tostr': 'and { eq { hop { nth_argmin { all_rows ; rank ; 3 } ; nation } ; japan ( jpn ) } ; eq { hop { nth_argmin { all_rows ; rank ; 3 } ; silver } ; 1 } }', 'tointer': 'the nation record of the row with 3rd minimum rank record is japan ( jpn ) . the silver record of the row with 3rd minimum rank record is 1 .'}], 'result': True, 'ind': 8, 'tostr': 'and { eq { nth_min { all_rows ; rank ; 3 } ; 3 } ; and { eq { hop { nth_argmin { all_rows ; rank ; 3 } ; nation } ; japan ( jpn ) } ; eq { hop { nth_argmin { all_rows ; rank ; 3 } ; silver } ; 1 } } } = true', 'tointer': 'the 3rd minimum rank record of all rows is 3 . the nation record of the row with 3rd minimum rank record is japan ( jpn ) . the silver record of the row with 3rd minimum rank record is 1 .'}

and { eq { nth_min { all_rows ; rank ; 3 } ; 3 } ; and { eq { hop { nth_argmin { all_rows ; rank ; 3 } ; nation } ; japan ( jpn ) } ; eq { hop { nth_argmin { all_rows ; rank ; 3 } ; silver } ; 1 } } } = true

the 3rd minimum rank record of all rows is 3 . the nation record of the row with 3rd minimum rank record is japan ( jpn ) . the silver record of the row with 3rd minimum rank record is 1 .

10

9

{'and_8': 8, 'result_9': 9, 'eq_1': 1, 'nth_min_0': 0, 'all_rows_10': 10, 'rank_11': 11, '3_12': 12, '3_13': 13, 'and_7': 7, 'str_eq_4': 4, 'str_hop_3': 3, 'nth_argmin_2': 2, 'all_rows_14': 14, 'rank_15': 15, '3_16': 16, 'nation_17': 17, 'japan (jpn)_18': 18, 'eq_6': 6, 'num_hop_5': 5, 'silver_19': 19, '1_20': 20}

{'and_8': 'and', 'result_9': 'true', 'eq_1': 'eq', 'nth_min_0': 'nth_min', 'all_rows_10': 'all_rows', 'rank_11': 'rank', '3_12': '3', '3_13': '3', 'and_7': 'and', 'str_eq_4': 'str_eq', 'str_hop_3': 'str_hop', 'nth_argmin_2': 'nth_argmin', 'all_rows_14': 'all_rows', 'rank_15': 'rank', '3_16': '3', 'nation_17': 'nation', 'japan (jpn)_18': 'japan ( jpn )', 'eq_6': 'eq', 'num_hop_5': 'num_hop', 'silver_19': 'silver', '1_20': '1'}

{'and_8': [9], 'result_9': [], 'eq_1': [8], 'nth_min_0': [1], 'all_rows_10': [0], 'rank_11': [0], '3_12': [0], '3_13': [1], 'and_7': [8], 'str_eq_4': [7], 'str_hop_3': [4], 'nth_argmin_2': [3, 5], 'all_rows_14': [2], 'rank_15': [2], '3_16': [2], 'nation_17': [3], 'japan (jpn)_18': [4], 'eq_6': [7], 'num_hop_5': [6], 'silver_19': [5], '1_20': [6]}

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

[['1', 'south korea ( kor )', '2', '0', '0', '2'], ['2', 'chinese taipei ( tpe )', '0', '1', '1', '2'], ['3', 'japan ( jpn )', '0', '1', '0', '1'], ['4', 'thailand ( tha )', '0', '0', '1', '1'], ['total', 'total', '2', '2', '2', '6']]

utah jazz all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-11545282-4.html.csv

ordinal

james donaldson is the player with the latest year record of playing for the utah jazz .

{'row': '6', 'col': '4', 'order': '1', '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', 'years for jazz', '1'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; years for jazz ; 1 }'}, 'player'], 'result': 'james donaldson', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; years for jazz ; 1 } ; player }'}, 'james donaldson'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; years for jazz ; 1 } ; player } ; james donaldson } = true', 'tointer': 'select the row whose years for jazz record of all rows is 1st maximum . the player record of this row is james donaldson .'}

eq { hop { nth_argmax { all_rows ; years for jazz ; 1 } ; player } ; james donaldson } = true

select the row whose years for jazz record of all rows is 1st maximum . the player record of this row is james donaldson .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'years for jazz_5': 5, '1_6': 6, 'player_7': 7, 'james donaldson_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', 'years for jazz_5': 'years for jazz', '1_6': '1', 'player_7': 'player', 'james donaldson_8': 'james donaldson'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'years for jazz_5': [0], '1_6': [0], 'player_7': [1], 'james donaldson_8': [2]}

['player', 'nationality', 'position', 'years for jazz', 'school / club team']

[['adrian dantley', 'united states', 'guard - forward', '1979 - 86', 'notre dame'], ['brad davis', 'united states', 'guard', '1979 - 80', 'maryland'], ['darryl dawkins', 'united states', 'center', '1987 - 88', 'maynard evans hs'], ['paul dawkins', 'united states', 'guard', '1979 - 80', 'northern illinois'], ['greg deane', 'united states', 'guard', '1979 - 80', 'utah'], ['james donaldson', 'united states', 'center', '1993 , 1994 - 95', 'washington state'], ['john drew', 'united states', 'guard - forward', '1982 - 85', 'gardner - webb'], ['john duren', 'united states', 'guard', '1980 - 82', 'georgetown']]

albert county , new brunswick

https://en.wikipedia.org/wiki/Albert_County%2C_New_Brunswick

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-170958-2.html.csv

ordinal

the parish in albert county new brunswick with the second highest population is hillsborough .

{'row': '2', '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', 'population', '2'], 'result': None, 'ind': 0, 'tostr': 'nth_argmax { all_rows ; population ; 2 }'}, 'official name'], 'result': 'hillsborough', 'ind': 1, 'tostr': 'hop { nth_argmax { all_rows ; population ; 2 } ; official name }'}, 'hillsborough'], 'result': True, 'ind': 2, 'tostr': 'eq { hop { nth_argmax { all_rows ; population ; 2 } ; official name } ; hillsborough } = true', 'tointer': 'select the row whose population record of all rows is 2nd maximum . the official name record of this row is hillsborough .'}

eq { hop { nth_argmax { all_rows ; population ; 2 } ; official name } ; hillsborough } = true

select the row whose population record of all rows is 2nd maximum . the official name record of this row is hillsborough .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'nth_argmax_0': 0, 'all_rows_4': 4, 'population_5': 5, '2_6': 6, 'official name_7': 7, 'hillsborough_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', 'population_5': 'population', '2_6': '2', 'official name_7': 'official name', 'hillsborough_8': 'hillsborough'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'nth_argmax_0': [1], 'all_rows_4': [0], 'population_5': [0], '2_6': [0], 'official name_7': [1], 'hillsborough_8': [2]}

['official name', 'status', 'area km 2', 'population', 'census ranking']

[['coverdale', 'parish', '236.15', '4401', '769 of 5008'], ['hillsborough', 'parish', '303.73', '1395', '1684 of 5008'], ['elgin', 'parish', '519.38', '968', '2124 of 5008'], ['hopewell', 'parish', '149.32', '643', '2689 of 5008'], ['harvey', 'parish', '276.84', '376', '3372 of 5008'], ['alma', 'parish', '222.79', '0', '4932 of 5008']]

1967 south african grand prix

https://en.wikipedia.org/wiki/1967_South_African_Grand_Prix

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1122362-1.html.csv

count

at the 1967 south african grand prix , there were 2 drivers who completed 80 laps .

{'scope': 'all', 'criterion': 'equal', 'value': '80', 'result': '2', 'col': '3', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_eq', 'args': ['all_rows', 'laps', '80'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose laps record is equal to 80 .', 'tostr': 'filter_eq { all_rows ; laps ; 80 }'}], 'result': '2', 'ind': 1, 'tostr': 'count { filter_eq { all_rows ; laps ; 80 } }', 'tointer': 'select the rows whose laps record is equal to 80 . the number of such rows is 2 .'}, '2'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_eq { all_rows ; laps ; 80 } } ; 2 } = true', 'tointer': 'select the rows whose laps record is equal to 80 . the number of such rows is 2 .'}

eq { count { filter_eq { all_rows ; laps ; 80 } } ; 2 } = true

select the rows whose laps record is equal to 80 . 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, 'laps_5': 5, '80_6': 6, '2_7': 7}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_eq_0': 'filter_eq', 'all_rows_4': 'all_rows', 'laps_5': 'laps', '80_6': '80', '2_7': '2'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_eq_0': [1], 'all_rows_4': [0], 'laps_5': [0], '80_6': [0], '2_7': [2]}

['driver', 'constructor', 'laps', 'time / retired', 'grid']

[['pedro rodrã\xadguez', 'cooper - maserati', '80', '2:05:45.9', '4'], ['john love', 'cooper - climax', '80', '+ 26.4', '5'], ['john surtees', 'honda', '79', '+ 1 lap', '6'], ['denny hulme', 'brabham - repco', '78', '+ 2 laps', '2'], ['bob anderson', 'brabham - climax', '78', '+ 2 laps', '10'], ['jack brabham', 'brabham - repco', '76', '+ 4 laps', '1'], ['dave charlton', 'brabham - climax', '63', 'not classified', '8'], ['luki botha', 'brabham - climax', '60', 'not classified', '17'], ['sam tingle', 'lds - climax', '56', 'accident', '14'], ['piers courage', 'lotus - brm', '51', 'fuel system', '18'], ['dan gurney', 'eagle - climax', '44', 'suspension', '11'], ['jo siffert', 'cooper - maserati', '41', 'engine', '16'], ['jochen rindt', 'cooper - maserati', '38', 'engine', '7'], ['mike spence', 'brm', '31', 'oil leak', '13'], ['jo bonnier', 'cooper - maserati', '30', 'engine', '12'], ['jim clark', 'lotus - brm', '22', 'engine', '3'], ['graham hill', 'lotus - brm', '6', 'accident', '15'], ['jackie stewart', 'brm', '2', 'engine', '9']]

cryengine

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-1241866-2.html.csv

comparative

merchants of brooklyn was released after crysis warhead was released .

{'row_1': '5', 'row_2': '3', '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', 'title', 'merchants of brooklyn'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose title record fuzzily matches to merchants of brooklyn .', 'tostr': 'filter_eq { all_rows ; title ; merchants of brooklyn }'}, 'year'], 'result': None, 'ind': 2, 'tostr': 'hop { filter_eq { all_rows ; title ; merchants of brooklyn } ; year }', 'tointer': 'select the rows whose title record fuzzily matches to merchants of brooklyn . take the year record of this row .'}, {'func': 'num_hop', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'title', 'crysis warhead'], 'result': None, 'ind': 1, 'tointer': 'select the rows whose title record fuzzily matches to crysis warhead .', 'tostr': 'filter_eq { all_rows ; title ; crysis warhead }'}, 'year'], 'result': None, 'ind': 3, 'tostr': 'hop { filter_eq { all_rows ; title ; crysis warhead } ; year }', 'tointer': 'select the rows whose title record fuzzily matches to crysis warhead . take the year record of this row .'}], 'result': True, 'ind': 4, 'tostr': 'greater { hop { filter_eq { all_rows ; title ; merchants of brooklyn } ; year } ; hop { filter_eq { all_rows ; title ; crysis warhead } ; year } } = true', 'tointer': 'select the rows whose title record fuzzily matches to merchants of brooklyn . take the year record of this row . select the rows whose title record fuzzily matches to crysis warhead . take the year record of this row . the first record is greater than the second record .'}

greater { hop { filter_eq { all_rows ; title ; merchants of brooklyn } ; year } ; hop { filter_eq { all_rows ; title ; crysis warhead } ; year } } = true

select the rows whose title record fuzzily matches to merchants of brooklyn . take the year record of this row . select the rows whose title record fuzzily matches to crysis warhead . take the year 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, 'title_7': 7, 'merchants of brooklyn_8': 8, 'year_9': 9, 'num_hop_3': 3, 'filter_str_eq_1': 1, 'all_rows_10': 10, 'title_11': 11, 'crysis warhead_12': 12, 'year_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', 'title_7': 'title', 'merchants of brooklyn_8': 'merchants of brooklyn', 'year_9': 'year', 'num_hop_3': 'num_hop', 'filter_str_eq_1': 'filter_str_eq', 'all_rows_10': 'all_rows', 'title_11': 'title', 'crysis warhead_12': 'crysis warhead', 'year_13': 'year'}

{'greater_4': [5], 'result_5': [], 'num_hop_2': [4], 'filter_str_eq_0': [2], 'all_rows_6': [0], 'title_7': [0], 'merchants of brooklyn_8': [0], 'year_9': [2], 'num_hop_3': [4], 'filter_str_eq_1': [3], 'all_rows_10': [1], 'title_11': [1], 'crysis warhead_12': [1], 'year_13': [3]}

['title', 'year', 'developer', 'publisher', 'platform']

[['blue mars', '2009 ( open beta )', 'avatar reality', 'avatar reality', 'microsoft windows'], ['crysis', '2007', 'crytek frankfurt', 'electronic arts', 'microsoft windows'], ['crysis warhead', '2008', 'crytek budapest', 'electronic arts', 'microsoft windows'], ['entropia universe', '2003 ( initial version ) 2009 ( cryengine 2 version )', 'mindark', 'mindark', 'microsoft windows'], ['merchants of brooklyn', '2009', 'paleo entertainment', 'paleo entertainment', 'microsoft windows'], ['the day', 'tba', 'reloaded studios', 'nexon tencent holdings', 'microsoft windows'], ['vigilance', 'released', 'harrington group', 'harrington group', 'microsoft windows']]

2010 - 11 atlanta thrashers season

https://en.wikipedia.org/wiki/2010%E2%80%9311_Atlanta_Thrashers_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/1-27537518-6.html.csv

majority

in the 2010 -11 atlanta thrashers season , most of the matches at philips arena had o pavelec with the decision .

{'scope': 'subset', 'col': '6', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'o pavelec', 'subset': {'col': '7', 'criterion': 'equal', 'value': 'philips arena'}}

{'func': 'most_str_eq', 'args': [{'func': 'filter_str_eq', 'args': ['all_rows', 'location', 'philips arena'], 'result': None, 'ind': 0, 'tostr': 'filter_eq { all_rows ; location ; philips arena }', 'tointer': 'select the rows whose location record fuzzily matches to philips arena .'}, 'decision', 'o pavelec'], 'result': True, 'ind': 1, 'tointer': 'select the rows whose location record fuzzily matches to philips arena . for the decision records of these rows , most of them fuzzily match to o pavelec .', 'tostr': 'most_eq { filter_eq { all_rows ; location ; philips arena } ; decision ; o pavelec } = true'}

most_eq { filter_eq { all_rows ; location ; philips arena } ; decision ; o pavelec } = true

select the rows whose location record fuzzily matches to philips arena . for the decision records of these rows , most of them fuzzily match to o pavelec .

2

2

{'most_str_eq_1': 1, 'result_2': 2, 'filter_str_eq_0': 0, 'all_rows_3': 3, 'location_4': 4, 'philips arena_5': 5, 'decision_6': 6, 'o pavelec_7': 7}

{'most_str_eq_1': 'most_str_eq', 'result_2': 'true', 'filter_str_eq_0': 'filter_str_eq', 'all_rows_3': 'all_rows', 'location_4': 'location', 'philips arena_5': 'philips arena', 'decision_6': 'decision', 'o pavelec_7': 'o pavelec'}

{'most_str_eq_1': [2], 'result_2': [], 'filter_str_eq_0': [1], 'all_rows_3': [0], 'location_4': [0], 'philips arena_5': [0], 'decision_6': [1], 'o pavelec_7': [1]}

['game', 'date', 'opponent', 'score', 'first star', 'decision', 'location', 'attendance', 'record', 'points']

[['26', 'december 2', 'pittsburgh penguins', '2 - 3', 's crosby', 'o pavelec', 'consol energy center', '18223', '13 - 10 - 3', '29'], ['27', 'december 4', 'washington capitals', '3 - 1', 'o pavelec', 'o pavelec', 'verizon center', '18398', '14 - 10 - 3', '31'], ['28', 'december 6', 'nashville predators', '3 - 2 ot', 'z bogosian', 'o pavelec', 'philips arena', '10024', '15 - 10 - 3', '33'], ['29', 'december 10', 'colorado avalanche', '2 - 4', 'm duchene', 'o pavelec', 'philips arena', '14034', '15 - 11 - 3', '33'], ['30', 'december 11', 'new york islanders', '5 - 4', 'j oduya', 'c mason', 'nassau coliseum', '10056', '16 - 11 - 3', '35'], ['31', 'december 13', 'ottawa senators', '4 - 3 ot', 'b little', 'o pavelec', 'scotiabank place', '18184', '17 - 11 - 3', '37'], ['32', 'december 15', 'tampa bay lightning', '1 - 2 so', 's bergenheim', 'o pavelec', 'st pete times forum', '14441', '17 - 11 - 4', '38'], ['33', 'december 16', 'carolina hurricanes', '2 - 3 so', 's samsonov', 'c mason', 'philips arena', '11043', '17 - 11 - 5', '39'], ['34', 'december 18', 'new jersey devils', '7 - 1', 'e boulton', 'o pavelec', 'philips arena', '17024', '18 - 11 - 5', '41'], ['35', 'december 20', 'toronto maple leafs', '6 - 3', 't enstrom', 'o pavelec', 'air canada centre', '19301', '19 - 11 - 5', '43'], ['36', 'december 21', 'st louis blues', '2 - 4', 'a steen', 'c mason', 'philips arena', '14662', '19 - 12 - 5', '43'], ['37', 'december 23', 'boston bruins', '1 - 4', 's thornton', 'o pavelec', 'td garden', '17565', '19 - 13 - 5', '43'], ['38', 'december 26', 'tampa bay lightning', '2 - 3 ot', 'v lecavalier', 'o pavelec', 'philips arena', '14610', '19 - 13 - 6', '44'], ['39', 'december 28', 'pittsburgh penguins', '3 - 6', 's crosby', 'o pavelec', 'consol energy center', '18322', '19 - 14 - 6', '44'], ['40', 'december 30', 'boston bruins', '3 - 2 so', 't enstrom', 'o pavelec', 'philips arena', '17624', '20 - 14 - 6', '46']]

iran at the 1998 asian games

https://en.wikipedia.org/wiki/Iran_at_the_1998_Asian_Games

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10831471-37.html.csv

majority

most of the athletes did not advance to the final in iran at the 1998 asian games .

{'scope': 'all', 'col': '8', 'most_or_all': 'most', 'criterion': 'equal', 'value': 'did not advance', 'subset': None}

{'func': 'most_str_eq', 'args': ['all_rows', 'final', 'did not advance'], 'result': True, 'ind': 0, 'tointer': 'for the final records of all rows , most of them fuzzily match to did not advance .', 'tostr': 'most_eq { all_rows ; final ; did not advance } = true'}

most_eq { all_rows ; final ; did not advance } = true

for the final records of all rows , most of them fuzzily match to did not advance .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'final_3': 3, 'did not advance_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'final_3': 'final', 'did not advance_4': 'did not advance'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'final_3': [0], 'did not advance_4': [0]}

['athlete', 'event', 'round 1', 'round 2', 'round 3', 'round 4', 'round 5', 'final']

[['ali ashkani', '54 kg', 'suwanna w 10 - 0', 'wang l 4 - 9', 'repechage aripov l 2 - 3', 'did not advance', 'did not advance', 'did not advance'], ['sardar pashaei', '58 kg', 'tumasis w 12 - 0', '-', 'khudaiberdiev l 5 - 8', 'repechage nishimi w 3 - 2', 'n / a', '3rd place match sheng l 0 - 3'], ['parviz zeidvand', '63 kg', 'mamedov w 3 - 0', 'yi l 1 - 2 , dsq', 'did not advance', 'did not advance', 'did not advance', 'did not advance'], ['gholam hossein pezeshki', '69 kg', 'al - saleh w 5 - 0', '-', 'manukyan l 0 - 10', 'repechage jong l 2 - 3', 'n / a', 'did not advance'], ['mehdi rahimi', '76 kg', 'baiseitov l 0 - 4', 'repechage al - ken l 3 - 11', 'did not advance', 'did not advance', 'n / a', 'did not advance'], ['behrouz jamshidi', '85 kg', 'park l 2 - 4', 'repechage redjepov w 4 - 0', '-', 'repechage achilov w 7 - 0', 'n / a', '3rd place match yokoyama l 2 - 4'], ['mohammad sharabiani', '97 kg', 'matvienko l 0 - 3', 'repechage iwabuchi w 7 - 0', '-', 'repechage park l 0 - 4', 'n / a', 'did not advance'], ['mehdi sabzali', '130 kg', '-', 'zhao w 0 - 0', 'hamaue w 3 - 0', 'n / a', 'n / a', 'quziev w 6 - 3']]

1954 vfl season

https://en.wikipedia.org/wiki/1954_VFL_season

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-10773616-18.html.csv

count

there were 6 game venues used during the 1954 vfl season .

{'scope': 'all', 'criterion': 'all', 'value': 'n/a', 'result': '6', 'col': '5', 'subset': None}

{'func': 'eq', 'args': [{'func': 'count', 'args': [{'func': 'filter_all', 'args': ['all_rows', 'venue'], 'result': None, 'ind': 0, 'tointer': 'select the rows whose venue record is arbitrary .', 'tostr': 'filter_all { all_rows ; venue }'}], 'result': '6', 'ind': 1, 'tostr': 'count { filter_all { all_rows ; venue } }', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}, '6'], 'result': True, 'ind': 2, 'tostr': 'eq { count { filter_all { all_rows ; venue } } ; 6 } = true', 'tointer': 'select the rows whose venue record is arbitrary . the number of such rows is 6 .'}

eq { count { filter_all { all_rows ; venue } } ; 6 } = true

select the rows whose venue record is arbitrary . the number of such rows is 6 .

3

3

{'eq_2': 2, 'result_3': 3, 'count_1': 1, 'filter_all_0': 0, 'all_rows_4': 4, 'venue_5': 5, '6_6': 6}

{'eq_2': 'eq', 'result_3': 'true', 'count_1': 'count', 'filter_all_0': 'filter_all', 'all_rows_4': 'all_rows', 'venue_5': 'venue', '6_6': '6'}

{'eq_2': [3], 'result_3': [], 'count_1': [2], 'filter_all_0': [1], 'all_rows_4': [0], 'venue_5': [0], '6_6': [2]}

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

[['north melbourne', '19.15 ( 129 )', 'st kilda', '12.10 ( 82 )', 'arden street oval', '9500', '28 august 1954'], ['footscray', '17.15 ( 117 )', 'hawthorn', '5.4 ( 34 )', 'western oval', '22896', '28 august 1954'], ['south melbourne', '7.7 ( 49 )', 'melbourne', '14.17 ( 101 )', 'lake oval', '25000', '28 august 1954'], ['fitzroy', '14.13 ( 97 )', 'essendon', '13.13 ( 91 )', 'brunswick street oval', '20000', '28 august 1954'], ['richmond', '14.17 ( 101 )', 'collingwood', '6.12 ( 48 )', 'punt road oval', '25000', '28 august 1954'], ['geelong', '13.12 ( 90 )', 'carlton', '6.13 ( 49 )', 'kardinia park', '23119', '28 august 1954']]

vilnius marathon

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-18564507-1.html.csv

aggregation

the number of gold medals awarded at the vilnius marathon totaled 27 .

{'scope': 'all', 'col': '3', 'type': 'sum', 'result': '27', 'subset': None}

{'func': 'round_eq', 'args': [{'func': 'sum', 'args': ['all_rows', 'gold'], 'result': '27', 'ind': 0, 'tostr': 'sum { all_rows ; gold }'}, '27'], 'result': True, 'ind': 1, 'tostr': 'round_eq { sum { all_rows ; gold } ; 27 } = true', 'tointer': 'the sum of the gold record of all rows is 27 .'}

round_eq { sum { all_rows ; gold } ; 27 } = true

the sum of the gold record of all rows is 27 .

2

2

{'eq_1': 1, 'result_2': 2, 'sum_0': 0, 'all_rows_3': 3, 'gold_4': 4, '27_5': 5}

{'eq_1': 'eq', 'result_2': 'true', 'sum_0': 'sum', 'all_rows_3': 'all_rows', 'gold_4': 'gold', '27_5': '27'}

{'eq_1': [2], 'result_2': [], 'sum_0': [1], 'all_rows_3': [0], 'gold_4': [0], '27_5': [1]}

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

[['1', 'lithuania', '20', '20', '22', '62'], ['2', 'belarus', '5', '3', '3', '11'], ['3', 'latvia', '1', '1', '2', '4'], ['4', 'kenya', '1', '1', '0', '2'], ['5', 'poland', '0', '1', '0', '1'], ['5', 'germany', '0', '1', '0', '1'], ['5', 'australia', '0', '1', '0', '1'], ['8', 'estonia', '0', '0', '1', '1'], ['8', 'united kingdom', '0', '0', '1', '1']]

memphis grizzlies all - time roster

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-16494599-3.html.csv

superlative

pete chilcutt was the first of these players to join the grizzlies .

{'scope': 'all', 'col_superlative': '4', 'row_superlative': '5', 'value_mentioned': 'no', 'max_or_min': 'min', 'other_col': '1', 'subset': None}

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

eq { hop { argmin { all_rows ; years for grizzlies } ; player } ; pete chilcutt } = true

select the row whose years for grizzlies record of all rows is minimum . the player record of this row is pete chilcutt .

3

3

{'str_eq_2': 2, 'result_3': 3, 'str_hop_1': 1, 'argmin_0': 0, 'all_rows_4': 4, 'years for grizzlies_5': 5, 'player_6': 6, 'pete chilcutt_7': 7}

{'str_eq_2': 'str_eq', 'result_3': 'true', 'str_hop_1': 'str_hop', 'argmin_0': 'argmin', 'all_rows_4': 'all_rows', 'years for grizzlies_5': 'years for grizzlies', 'player_6': 'player', 'pete chilcutt_7': 'pete chilcutt'}

{'str_eq_2': [3], 'result_3': [], 'str_hop_1': [2], 'argmin_0': [1], 'all_rows_4': [0], 'years for grizzlies_5': [0], 'player_6': [1], 'pete chilcutt_7': [2]}

['player', 'nationality', 'position', 'years for grizzlies', 'school / club team']

[['brian cardinal', 'united states', 'forward', '2004 - 2008', 'purdue'], ['rodney carney', 'united states', 'forward', '2011', 'memphis'], ['antoine carr', 'united states', 'forward / center', '1999 - 2000', 'wichita state'], ['demarre carroll', 'united states', 'forward', '2009 - 2012', 'missouri'], ['pete chilcutt', 'united states', 'power forward', '1996 - 1999', 'north carolina'], ['jason collins', 'united states', 'center', '2008', 'stanford'], ['mike conley , jr', 'united states', 'point guard', '2007present', 'ohio state'], ['will conroy', 'united states', 'guard', '2007', 'washington'], ['javaris crittenton', 'united states', 'point guard', '2008', 'georgia tech'], ['dante cunningham', 'united states', 'forward', '2011 - 2012', 'villanova']]

eren derdiyok

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

https://raw.githubusercontent.com/wenhuchen/Table-Fact-Checking/master/data/all_csv/2-12318000-2.html.csv

majority

most of the competitions for eren derdiyok were in the category of friendly competition .

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

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

most_eq { all_rows ; competition ; friendly } = true

for the competition records of all rows , most of them fuzzily match to friendly .

1

1

{'most_str_eq_0': 0, 'result_1': 1, 'all_rows_2': 2, 'competition_3': 3, 'friendly_4': 4}

{'most_str_eq_0': 'most_str_eq', 'result_1': 'true', 'all_rows_2': 'all_rows', 'competition_3': 'competition', 'friendly_4': 'friendly'}

{'most_str_eq_0': [1], 'result_1': [], 'all_rows_2': [0], 'competition_3': [0], 'friendly_4': [0]}

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

[['6 february 2008', 'london , england', '1 - 1', '2 - 1', 'friendly'], ['9 september 2009', 'riga , latvia', '2 - 2', '2 - 2', '2010 fifa world cup qualification'], ['10 august 2011', 'vaduz , liechtenstein', '1 - 0', '1 - 2', 'friendly'], ['11 october 2011', 'basel , switzerland', '1 - 0', '2 - 0', 'uefa euro 2012 qualifying'], ['26 may 2012', 'basel , switzerland', '1 - 0', '5 - 3', 'friendly'], ['26 may 2012', 'basel , switzerland', '2 - 0', '5 - 3', 'friendly'], ['26 may 2012', 'basel , switzerland', '3 - 1', '5 - 3', 'friendly'], ['14 november 2012', 'sousse , tunisia', '1 - 0', '2 - 1', 'friendly']]