---
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.