| --- |
| license: cc-by-sa-4.0 |
| language: |
| - en |
| task_categories: |
| - text-generation |
| tags: |
| - relation-extraction |
| - wikidata |
| - wikipedia |
| - knowledge-graph |
| - information-extraction |
| size_categories: |
| - 1M<n<10M |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: train.jsonl |
| - split: validation |
| path: valid.jsonl |
| - split: test |
| path: test.jsonl |
| --- |
| |
| # COVERED-data |
|
|
| COVERED aligns Wikipedia sentences with Wikidata triples for benchmarking generative relation extraction. It is built with the WikiS2T framework. |
|
|
| ## Statistics |
|
|
| | Split | Sentences | Triples | Entities | Relations | |
| |---|---:|---:|---:|---:| |
| | all | 2,382,570 | 4,863,548 | 307,146 | 1,139 | |
| | train | 1,909,789 | 3,898,094 | 245,716 | 1,106 | |
| | valid | 238,719 | 485,865 | 30,713 | 746 | |
| | test | 234,062 | 479,589 | 30,717 | 752 | |
|
|
| The split is done at the entity level and stratified by category (80/10/10, seed 42). All sentences of an entity are in the same split. |
|
|
| ## Categories |
|
|
| 17 Wikidata categories (selected by P31 *instance of*): 12 general and 5 domain-specific, sorted by number of sentences. |
|
|
| | Category | Group | Entities | Sentences | Triples | Sentences per entity | |
| |---|---|---:|---:|---:|---:| |
| | human | general | 27,919 | 1,068,288 | 2,099,478 | 38.26 | |
| | film | general | 27,119 | 281,062 | 679,600 | 10.36 | |
| | album | general | 25,163 | 176,853 | 378,261 | 7.03 | |
| | river | general | 28,082 | 151,683 | 314,948 | 5.40 | |
| | literary_work | general | 26,037 | 126,154 | 286,555 | 4.85 | |
| | business | general | 24,951 | 120,977 | 200,681 | 4.85 | |
| | building | general | 17,921 | 74,550 | 124,268 | 4.16 | |
| | taxon | domain-specific | 24,434 | 69,757 | 137,885 | 2.85 | |
| | organization | general | 18,053 | 63,992 | 100,237 | 3.54 | |
| | mountain | general | 24,953 | 63,734 | 141,636 | 2.55 | |
| | human_settlement | general | 25,247 | 46,661 | 107,502 | 1.85 | |
| | painting | general | 9,057 | 42,498 | 112,950 | 4.69 | |
| | street | general | 4,114 | 29,171 | 52,359 | 7.09 | |
| | chemical | domain-specific | 8,523 | 24,386 | 39,200 | 2.86 | |
| | gene | domain-specific | 9,443 | 22,341 | 52,554 | 2.37 | |
| | asteroid | domain-specific | 4,183 | 13,391 | 23,310 | 3.20 | |
| | star | domain-specific | 1,947 | 7,072 | 12,124 | 3.63 | |
| | **All** | | 307,146 | 2,382,570 | 4,863,548 | 7.76 | |
|
|
| ## Format |
|
|
| One JSON object per line, one sentence per object. |
|
|
| ```json |
| { |
| "category": "album", |
| "entity": "Q100234970_Utopia", |
| "sentence_id": "1_0", |
| "sentence": "Utopia is the fourth studio album by American rapper Travis Scott.", |
| "triples": [ |
| {"hop": 1, "triple_index": 11, "subject_id": "Q100234970", "subject_label": "Utopia", |
| "predicate_id": "P175", "predicate_label": "performer", |
| "object_id": "Q13605596", "object_label": "Travis Scott"}, |
| {"hop": 2, "subject_id": "Q13605596", "subject_label": "Travis Scott", |
| "predicate_id": "P106", "predicate_label": "occupation", |
| "object_id": "Q2252262", "object_label": "rapper", "via_object_id": "Q13605596"} |
| ] |
| } |
| ``` |
|
|
| | Field | Meaning | |
| |---|---| |
| | `category` | One of the 17 categories above | |
| | `entity` | Source entity, `<QID>_<title>` | |
| | `sentence_id` | Sentence index in the entity's article | |
| | `sentence` | Wikipedia sentence | |
| | `triples[].hop` | 1: subject is the source entity. 2: subject is an entity object of a 1-hop triple aligned to this sentence | |
| | `triples[].subject_id`, `predicate_id`, `object_id` | Wikidata ids | |
| | `triples[].*_label` | English labels | |
| | `triples[].object_id` | Empty string for literal objects (dates, quantities, text); the literal value is in `object_label` | |
| | `triples[].via_object_id` | 2-hop only: the entity through which the triple is reached | |
|
|
| ## License |
|
|
| The sentences come from Wikipedia and are released under CC BY-SA 4.0. Wikidata triples are CC0. |
|
|
