Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?

Michal Novák, Miloslav Konopik, Anna Nedoluzhko, Martin Popel, Ondrej Prazak, Jakub Sido, Milan Straka, Zdeněk Žabokrtský, Daniel Zeman


Abstract
The paper presents an overview of the fourth edition of the Shared Task on Multilingual Coreference Resolution, organized as part of the CODI-CRAC 2025 workshop. As in the previous editions, participants were challenged to develop systems that identify mentions and cluster them according to identity coreference. A key innovation of this year’s task was the introduction of a dedicated Large Language Model (LLM) track, featuring a simplified plaintext format designed to be more suitable for LLMs than the original CoNLL-U representation. The task also expanded its coverage with three new datasets in two additional languages, using version 1.3 of CorefUD – a harmonized multilingual collection of 22 datasets in 17 languages. In total, nine systems participated, including four LLM-based approaches (two fine-tuned and two using few-shot adaptation). While traditional systems still kept the lead, LLMs showed clear potential, suggesting they may soon challenge established approaches in future editions.
Anthology ID:
2025.crac-1.9
Volume:
Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference
Month:
November
Year:
2025
Address:
Suzhou, China
Editors:
Maciej Ogrodniczuk, Michal Novak, Massimo Poesio, Sameer Pradhan, Vincent Ng
Venue:
CRAC
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
95–118
Language:
URL:
https://aclanthology.org/2025.crac-1.9/
DOI:
Bibkey:
Cite (ACL):
Michal Novák, Miloslav Konopik, Anna Nedoluzhko, Martin Popel, Ondrej Prazak, Jakub Sido, Milan Straka, Zdeněk Žabokrtský, and Daniel Zeman. 2025. Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches?. In Proceedings of the Eighth Workshop on Computational Models of Reference, Anaphora and Coreference, pages 95–118, Suzhou, China. Association for Computational Linguistics.
Cite (Informal):
Findings of the Fourth Shared Task on Multilingual Coreference Resolution: Can LLMs Dethrone Traditional Approaches? (Novák et al., CRAC 2025)
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PDF:
https://aclanthology.org/2025.crac-1.9.pdf