---
title: "Multilingual Coreference Resolution in — Mishra 2024"
description: "Coreference resolution, which links text spans that refer to the same entity, is well developed for English, but South Asian languages have almost no…"
authors: ["Ritwik Mishra", "Pooja Desur", "Rajiv Ratn Shah", "Ponnurangam Kumaraguru"]
year: 2024
venue: "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)"
source: "https://aclanthology.org/2024.lrec-main.1031/"
arxiv: "2402.13571"
licence: "CC BY-NC 4.0 (ELRA, LREC proceedings)"
licence_url: "https://creativecommons.org/licenses/by-nc/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/mishra-2024-multilingual-coreference-resolution-low-resource/"
---
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# Multilingual Coreference Resolution in Low-resource South Asian Languages

**Authors:** Ritwik Mishra, Pooja Desur, [Rajiv Ratn Shah](https://md.research.elamur.ai/free/en/authors/rajiv-ratn-shah/), Ponnurangam Kumaraguru · **Year:** 2024 · **Venue:** Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) · **Licence:** [CC BY-NC 4.0 (ELRA, LREC proceedings)](https://creativecommons.org/licenses/by-nc/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2024.lrec-main.1031/) · [PDF](https://aclanthology.org/2024.lrec-main.1031.pdf) · [arXiv 2402.13571](https://arxiv.org/abs/2402.13571) · [OpenAlex](https://openalex.org/W7131822416)

**Citations:** 3 citations (openalex-snapshot · 2026-10-14) · 4 in our library, of the 140673 papers whose bibliographies we read

## Summary
Coreference resolution, which links text spans that refer to the same entity, is well developed for English, but South Asian languages have almost no public datasets or tools for it. The authors address this by building TransMuCoRes, a silver-standard corpus covering 31 South Asian languages. They took the English OntoNotes and LitBank datasets (LitBank adds singleton mentions), machine-translated the sentences with NLLB-200 models, and projected mention spans with awesome-align. Spans that mapped to non-contiguous words, or to no words at all, were discarded. They then fine-tuned two existing end-to-end systems, wl-coref and fast-coref, using either XLM-RoBERTa or mBERT encoders. Training combined TransMuCoRes with the manually annotated Hindi dataset of Mujadia et al. (2016). On a held-out test split of that Hindi gold data, the best model reached 64 LEA F1 and 68 CoNLL F1. According to the authors, this is the first end-to-end coreference evaluation on Hindi gold annotations. The released data and checkpoints give low-resource languages a starting point. The authors also point out that standard metrics handle split antecedents poorly.

## Key points
- **Translation pipeline:** Sentences were translated with nllb-200-1.3B. Outputs that failed a sanity check (mostly repeated punctuation) were re-translated with nllb-200-3.3B. After this step, only 111 of more than 3 million translations still failed, and roughly 12% of those failures were Sindhi.
- **Alignment method:** The high-recall awesome-align checkpoint aligned more mentions than simalign. About 75% of English mentions map to a contiguous span in the translation.
- **Split antecedents:** They account for a similar share of mentions in TransMuCoRes (2.4%) and in the Mujadia et al. (2016) Hindi set (2.7%).
- **Model comparison:** On the Hindi gold data, wl-coref clearly outperforms fast-coref. Across the translated languages, fast-coref tends to score higher. Results are very low for languages such as Santali, Dzongkha, Tibetan and Uyghur.
- **Singletons:** Both models improve when singletons are excluded from scoring, which shows that singleton mentions are a weak point. The authors call for models with higher mention-detection recall.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

Fields: [Linguistics & languages](https://md.research.elamur.ai/free/en/shelves/linguistics/)

Topics: [Coreference resolution](https://md.research.elamur.ai/free/en/topics/coreference-resolution/)

## Cite

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{mishra2024multilingual,
  title = {{Multilingual Coreference Resolution in Low-resource South Asian Languages}},
  author = {Mishra, Ritwik and Desur, Pooja and Shah, Rajiv Ratn and Kumaraguru, Ponnurangam},
  booktitle = {Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
  year = {2024},
  doi = {10.63317/5a8noeqwzx3e},
  eprint = {2402.13571},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.63317/5a8noeqwzx3e}
}
```

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- [↑ back to papers of 2024](https://md.research.elamur.ai/free/en/papers/2024/page/3/)

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