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# Do UD Trees Match Mention Spans in Coreference Annotations?

**Authors:** [Martin Popel](https://md.mova.elamur.ai/free/en/docs/papers/authors/martin-popel/), [Zdeněk Žabokrtský](https://md.mova.elamur.ai/free/en/docs/papers/authors/zdenek-zabokrtsku/), [Anna Nedoluzhko](https://md.mova.elamur.ai/free/en/docs/papers/authors/anna-nedoluzhko/), [Michal Novák](https://md.mova.elamur.ai/free/en/docs/papers/authors/michal-novak/), [Daniel Zeman](https://md.mova.elamur.ai/free/en/docs/papers/authors/daniel-zeman/) · **Year:** 2021 · **Venue:** Findings of the Association for Computational Linguistics: EMNLP 2021 **Link:** [aclanthology.org/2021.findings-emnlp.303](https://aclanthology.org/2021.findings-emnlp.303/) · **Licence:** [CC BY 4.0](https://creativecommons.org/licenses/by/4.0/)

[**0** citations](https://openalex.org/works?filter=cites:W3211720618) openalex · 2026-10-18[**3** citations in our library](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/coref-2021-popel-do-ud-trees-match-mention/) of the 140673 papers whose bibliographies we read[Findings of the Association for Computational Linguistics: EMNLP 2021](https://aclanthology.org/volumes/2021.findings-emnlp/)[licence](https://creativecommons.org/licenses/by/4.0/)

- [Publisher's page](https://aclanthology.org/2021.findings-emnlp.303/)
- [PDF](https://aclanthology.org/2021.findings-emnlp.303.pdf)
- [DOI 10.18653/v1/2021.findings-emnlp.303](https://doi.org/10.18653/v1/2021.findings-emnlp.303)
- [OpenAlex](https://openalex.org/W3211720618)

**Authors (5)**

1. [Martin Popel](https://openalex.org/A5083887502) [ORCID](https://orcid.org/0000-0002-3628-8419) · h 21 · 2689 citations · 110 works
2. [Zdeněk Žabokrtský](https://openalex.org/A5088317432) [ORCID](https://orcid.org/0000-0001-8149-4054) · h 23 · 2057 citations · 167 works
3. [Anna Nedoluzhko](https://openalex.org/A5036751057) [ORCID](https://orcid.org/0000-0003-0110-500X) · h 11 · 800 citations · 101 works
4. [Michal Novák](https://openalex.org/A5064242107) [ORCID](https://orcid.org/0000-0002-6052-7459) · h 10 · 416 citations · 63 works
5. [Daniel Zeman](https://openalex.org/A5061392927) [ORCID](https://orcid.org/0000-0002-5791-6568) · h 28 · 4506 citations · 176 works

Citations and author metrics from openalex (2026-10-18); authors with the same name are not always told apart.

## What it is about

Coreference mention spans in most corpora are plain token intervals, drawn without reference to syntax. The paper asks how often those spans match the subtrees of UD trees. It hand-checks mismatches in nine CorefUD datasets for eight languages. In eight of the nine, the trees come from UDPipe; English-GUM is the only one with hand-annotated trees. Most mentions (86% to 98%, depending on the dataset) are catenae, that is, connected parts of the tree. Among the remaining mismatches, more than half come from wrong trees, most often a case-marked nominal attached to the clause predicate instead of to the noun it modifies. The rest come from coordination, flat multiword names and span errors. The authors suggest that the mismatches can be used to find errors on either side.

## Ideas

- I1. `prag` / `world`: measure the share of entity mentions that are catenae in the trees Mova builds, on GUM test (test only) and on silver dev; the paper's range (86% to 98%) is the reference.
- I2. `tools/treeagree`: add a gate for the "generalized PP attachment" error, a case-marked nominal attached to a verb when a nominal head is available, and report violations per 1k sentences from `treeagree check` on silver dev.
- I3. `en/src/ctx.rs`: add a feature for the syntactic head of a mention, not the whole span, for pronoun-antecedent agreement, and measure agreement errors on a small hand-marked dev set.
- I4. `annot`: when a coreference span from `corpus/` is not a catena, send the sentence with the tree and the span to the teacher, and let the Rust gate decide; count how often the tree witnesses in `tools/parsecmp` side with the tree.

## More ideas (a second reading)

- I5. Use gold coreference spans as a free check of Mova's parser: on GUM dev, compute for every gold mention whether it is a catena in the SLM tree (`en annotate` output via `--trees`). Non-catena mentions are mostly parser errors, typically PP attachment; list them by error type and feed the list to the parser's repair work (the absurdity-matrix repairs in `world`). Report the non-catena rate for gold vs SLM trees as one number per parser version.
- I6. The same check on Mova's own coreference output: a chain whose mentions are all catenae in the SLM tree but whose antecedent mention crosses an attachment the parser got wrong (e.g. reference numbers as `appos`, the third error type in [coref — SLM coreference: a sieve of rules with a reason for every link](https://md.mova.elamur.ai/free/en/docs/coref/)) can be flagged in `coref explain`, so that link errors caused by trees are separated from sieve errors in the error analysis.

## For Mova

The ideas touch the mention output of `prag` and `world`, the context features of `en/src/ctx.rs` and the gates of `tools/treeagree`. The relevant chapters are [22. Phrases: noun, adjective, adverb and prepositional phrases](https://md.mova.elamur.ai/free/en/docs/languages/en/22-phrases/) (what a phrase covers) and `12-pronouns-determiners-numerals.md` (the head that carries agreement). The first measure is I1 on GUM test and silver dev, compared with the paper's catena rates.

Topics: [Coreference resolution](https://md.mova.elamur.ai/free/en/docs/papers/topics/coreference-resolution/) · [Universal Dependencies](https://md.mova.elamur.ai/free/en/docs/papers/topics/universal-dependencies/)

## Cite

The paper itself, not this card. BibTeX from the library's record of the work. [DOI 10.18653/v1/2021.findings-emnlp.303](https://doi.org/10.18653/v1/2021.findings-emnlp.303)

```
@inproceedings{popel2021do,
  title = {{Do UD Trees Match Mention Spans in Coreference Annotations?}},
  author = {Popel, Martin and Žabokrtský, Zdeněk and Nedoluzhko, Anna and Novák, Michal and Zeman, Daniel},
  booktitle = {Findings of the Association for Computational Linguistics: EMNLP 2021},
  year = {2021},
  doi = {10.18653/v1/2021.findings-emnlp.303},
  url = {https://doi.org/10.18653/v1/2021.findings-emnlp.303}
}
```

- [← previous Raising and resolving issues with scalar modifiers](https://md.mova.elamur.ai/free/en/docs/papers/coppock-2013-raising-resolving-issues-scalar-modifiers/)
- [next → Are we there yet? Encoder-decoder neural networks as cognitive models of English past tense inflection](https://md.mova.elamur.ai/free/en/docs/papers/corkery-2019-are-we-there-yet-encoder/)
- [↑ back to English](https://md.mova.elamur.ai/free/en/docs/papers/en/)

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