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# WikiCoref: An English Coreference-annotated Corpus of Wikipedia Articles

**Authors:** Abbas Ghaddar, Phillippe Langlais · **Year:** 2016 · **Venue:** Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC 2016) **Link:** [aclanthology.org/L16-1021](https://aclanthology.org/L16-1021/) · **Licence:** [CC BY-NC 4.0](https://creativecommons.org/licenses/by-nc/4.0/) (ELRA, LREC proceedings) — summary only; evaluation only for the data

[**70** citations](https://openalex.org/works?filter=cites:W2574762171) openalex · 2026-10-19[**49** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/ghaddar-2016-wikicoref-english-coreference-annotated-corpus/) of the 140673 papers whose bibliographies we read[Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)](https://aclanthology.org/volumes/L16-1/)[licence](https://creativecommons.org/licenses/by-nc/4.0/)

- [Publisher's page](https://aclanthology.org/L16-1021/)
- [PDF](https://aclanthology.org/L16-1021.pdf)
- [DOI 10.63317/3yjtmzi2qxqk](https://doi.org/10.63317/3yjtmzi2qxqk)
- [OpenAlex](https://openalex.org/W2574762171)

**Authors (2)**

1. [Abbas Ghaddar](https://openalex.org/A5044793533) [Semantic Scholar](https://www.semanticscholar.org/author/3448973) · h 11 · 378 citations · 50 works
2. [Phillippe Langlais](https://openalex.org/A5015070080) [Semantic Scholar](https://www.semanticscholar.org/author/1724343955) · h 8 · 307 citations · 24 works

Citations and author metrics from openalex (2026-10-19); authors with the same name are not always told apart.

## What it is about

WikiCoref is an English coreference corpus of Wikipedia articles, a genre that earlier corpora covered little, since most of them are newswire. The annotation follows OntoNotes with some changes. Each markable has a coreference type, a mention type and, for each chain, the equivalent Freebase topic. The first release has 30 documents, 59,652 tokens and 2,229 sentences, from 209 to 9,869 tokens each. The mention extent is the maximal one, so it includes pre-modifiers, post-modifiers and relative clauses. Agreement between two annotators is a Cohen's kappa of 0.78 on mention identification, and a MUC F1 of 83.3%. The authors call both values fair agreement.

## Ideas

- I1. Use the maximal-extent rule as a test for `coref/src/mention.rs`: a mention should span the full UD subtree of its head, minus the determiner where the paper excludes it. Report the share of mentions whose span differs and why.
- I2. Run the coreference sieve on the 30 documents, with the scores split by document length, to see whether the errors come from the long documents. Keep the 30 documents as an evaluation set, not for development.
- I3. Link each chain to a world entity, as the paper links chains to Freebase topics, using Mova's knowledge base in `world/src/knowledge.rs`. Count how many chains find an entity and how many stay unlinked.
- I4. Repeat the paper's double annotation with Mova's own output against a human check on 20 documents, and report kappa and MUC F1 together.

## For Mova

The chapter is [35. Reference and coreference](https://md.mova.elamur.ai/free/en/docs/languages/en/35-reference-and-coreference/). The code is `coref/src/mention.rs` and `coref/src/sieve.rs`, with the entity links in `world`. The measure is MUC F1 and CoNLL coreference F1 on the held-out documents, run twice. The corpus is NC-licensed, so it is used for evaluation only.

Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) · [Treebanks](https://md.mova.elamur.ai/free/en/docs/papers/topics/treebanks/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.63317/3yjtmzi2qxqk](https://doi.org/10.63317/3yjtmzi2qxqk)

```
@inproceedings{ghaddar2016wikicoref,
  title = {{WikiCoref: An English Coreference-annotated Corpus of Wikipedia Articles}},
  author = {Ghaddar, Abbas and Langlais, Phillippe},
  booktitle = {Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
  year = {2016},
  doi = {10.63317/3yjtmzi2qxqk},
  url = {https://doi.org/10.63317/3yjtmzi2qxqk}
}
```

- [← previous A Discourse Signal Annotation System for RST Trees](https://md.mova.elamur.ai/free/en/docs/papers/gessler-2019-discourse-signal-annotation-system-rst/)
- [next → Interpreting Verbal Irony: Linguistic Strategies and the Connection to the Type of Semantic Incongruity](https://md.mova.elamur.ai/free/en/docs/papers/ghosh-2020-interpreting-verbal-irony-linguistic-strategies/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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