fix readme
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- .gitattributes +48 -0
- README.md +24 -5
- check_split.py +26 -0
- create_split.py +0 -0
- data/{t_rex.filter_unified.min_entity_12_max_predicate_50.jsonl → t_rex.filter_unified.min_entity_12_max_predicate_10.test.jsonl} +2 -2
- data/{t_rex.filter_unified.min_entity_12_max_predicate_10.jsonl → t_rex.filter_unified.min_entity_12_max_predicate_10.train.jsonl} +2 -2
- data/{t_rex.filter_unified.min_entity_12_max_predicate_100.jsonl → t_rex.filter_unified.min_entity_12_max_predicate_10.validation.jsonl} +2 -2
- data/{t_rex.filter_unified.min_entity_12_max_predicate_25.jsonl → t_rex.filter_unified.min_entity_12_max_predicate_100.test.jsonl} +2 -2
- data/t_rex.filter_unified.min_entity_12_max_predicate_100.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_100.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_25.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_25.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_25.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_50.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_50.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_12_max_predicate_50.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_10.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_16_max_predicate_10.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_10.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_10.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_100.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_16_max_predicate_100.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_100.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_100.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_25.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_16_max_predicate_25.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_25.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_25.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_50.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_16_max_predicate_50.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_50.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_16_max_predicate_50.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_10.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_4_max_predicate_10.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_10.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_10.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_100.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_4_max_predicate_100.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_100.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_100.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_25.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_4_max_predicate_25.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_25.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_25.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_50.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_4_max_predicate_50.test.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_50.train.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_4_max_predicate_50.validation.jsonl +3 -0
- data/t_rex.filter_unified.min_entity_8_max_predicate_10.jsonl +0 -3
- data/t_rex.filter_unified.min_entity_8_max_predicate_10.test.jsonl +3 -0
.gitattributes
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@@ -96,3 +96,51 @@ data/t_rex.filter_unified.min_entity_12_max_predicate_10.jsonl filter=lfs diff=l
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data/t_rex.filter_unified.min_entity_12_max_predicate_100.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_50.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_100.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_100.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_50.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_100.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_25.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_10.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_25.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_100.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_100.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_100.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_50.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_10.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_100.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_50.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_25.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_100.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_25.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_50.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_10.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_25.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_50.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_25.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_10.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_10.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_50.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_25.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_50.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_50.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_10.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_10.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_100.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_50.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_10.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_100.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_50.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_100.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_25.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_50.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_10.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_100.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_25.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_50.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_100.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_10.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_10.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_100.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_25.test.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_8_max_predicate_25.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_4_max_predicate_25.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_100.train.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_16_max_predicate_50.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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data/t_rex.filter_unified.min_entity_12_max_predicate_10.validation.jsonl filter=lfs diff=lfs merge=lfs -text
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README.md
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This is the T-REX dataset proposed in [https://aclanthology.org/L18-1544/](https://aclanthology.org/L18-1544/).
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We split the raw T-REX dataset into train/validation/test split by the ratio of 70/15/15.
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### Filtering to Remove Noise
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We apply filtering to keep triples with alpha-numeric subject and object, as well as triples with at least either of subject or object is a named-entity.
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An example looks as follows.
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```
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{
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}
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```
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This is the T-REX dataset proposed in [https://aclanthology.org/L18-1544/](https://aclanthology.org/L18-1544/).
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We split the raw T-REX dataset into train/validation/test split by the ratio of 70/15/15.
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| data | train | validation | test | total |
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|:-----------------------------------------------|--------:|-------------:|-------:|--------:|
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| filter_unified.min_entity_4_max_predicate_100 | 7,790 | 865 | 2,113 | 10,768 |
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| filter_unified.min_entity_4_max_predicate_50 | 4,852 | 539 | 1,326 | 6,717 |
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| filter_unified.min_entity_4_max_predicate_25 | 2,874 | 319 | 768 | 3,961 |
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| filter_unified.min_entity_4_max_predicate_10 | 1,286 | 142 | 353 | 1,781 |
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| filter_unified.min_entity_8_max_predicate_100 | 6,117 | 679 | 1,647 | 8,443 |
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| filter_unified.min_entity_8_max_predicate_50 | 3,823 | 424 | 1,039 | 5,286 |
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| filter_unified.min_entity_8_max_predicate_25 | 2,319 | 257 | 640 | 3,216 |
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| filter_unified.min_entity_8_max_predicate_10 | 1,098 | 122 | 302 | 1,522 |
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| filter_unified.min_entity_12_max_predicate_100 | 5,186 | 576 | 1,429 | 7,191 |
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| filter_unified.min_entity_12_max_predicate_50 | 3,250 | 361 | 894 | 4,505 |
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| filter_unified.min_entity_12_max_predicate_25 | 1,971 | 218 | 531 | 2,720 |
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| filter_unified.min_entity_12_max_predicate_10 | 937 | 104 | 260 | 1,301 |
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| filter_unified.min_entity_16_max_predicate_100 | 4,690 | 521 | 1,270 | 6,481 |
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| filter_unified.min_entity_16_max_predicate_50 | 2,894 | 321 | 779 | 3,994 |
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| filter_unified.min_entity_16_max_predicate_25 | 1,734 | 192 | 463 | 2,389 |
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| filter_unified.min_entity_16_max_predicate_10 | 809 | 89 | 222 | 1,120 |
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### Filtering to Remove Noise
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We apply filtering to keep triples with alpha-numeric subject and object, as well as triples with at least either of subject or object is a named-entity.
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An example looks as follows.
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```
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{
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"object": "Persian",
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"subject": "Tajik",
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"title": "Tandoor bread",
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"text": "Tandoor bread (Arabic: \u062e\u0628\u0632 \u062a\u0646\u0648\u0631 khubz tannoor, Armenian: \u0569\u0578\u0576\u056b\u0580 \u0570\u0561\u0581 tonir hats, Azerbaijani: T\u0259ndir \u00e7\u00f6r\u0259yi, Georgian: \u10d7\u10dd\u10dc\u10d8\u10e1 \u10de\u10e3\u10e0\u10d8 tonis puri, Kazakh: \u0442\u0430\u043d\u0434\u044b\u0440 \u043d\u0430\u043d tandyr nan, Kyrgyz: \u0442\u0430\u043d\u0434\u044b\u0440 \u043d\u0430\u043d tandyr nan, Persian: \u0646\u0627\u0646 \u062a\u0646\u0648\u0631\u06cc nan-e-tanuri, Tajik: \u043d\u043e\u043d\u0438 \u0442\u0430\u043d\u0443\u0440\u0439 noni tanuri, Turkish: Tand\u0131r ekme\u011fi, Uyghur: ) is a type of leavened bread baked in a clay oven called a tandoor, similar to naan. In Pakistan, tandoor breads are popular especially in the Khyber Pakhtunkhwa and Punjab regions, where naan breads are baked in tandoor clay ovens fired by wood or charcoal. These tandoor-prepared naans are known as tandoori naan.",
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"predicate": "[Artifact] is a type of [Type]"
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}
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```
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check_split.py
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import json
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from itertools import product
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import pandas as pd
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parameters_min_e_freq = [4, 8, 12, 16]
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parameters_max_p_freq = [100, 50, 25, 10]
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stats = []
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for min_e_freq, max_p_freq in product(parameters_min_e_freq, parameters_max_p_freq):
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.train.jsonl") as f:
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train = [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.validation.jsonl") as f:
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validation = [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
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with open(f"data/t_rex.filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}.test.jsonl") as f:
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test = [json.loads(i) for i in f.read().split('\n') if len(i) > 0]
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stats.append({
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"data": f"filter_unified.min_entity_{min_e_freq}_max_predicate_{max_p_freq}",
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"train": len(train),
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"validation": len(validation),
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"test": len(test)
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})
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df = pd.DataFrame(stats)
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df['total'] = df['train'] + df['validation'] + df['test']
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print(df.to_markdown(index=False))
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create_split.py
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data/{t_rex.filter_unified.min_entity_12_max_predicate_50.jsonl → t_rex.filter_unified.min_entity_12_max_predicate_10.test.jsonl}
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