Findings of the Second Shared Task on Multilingual Coreference Resolution
CRAC 2023 Shared Task on Multilingual Coreference Resolution (2023)
Research topics:
Neural NetworksAbstract
This paper summarizes the second edition of the shared task on multilingual coreference resolution, held with the CRAC 2023 workshop. Just like last year, participants of the shared task were to create trainable systems that detect mentions and group them based on identity coreference; however, this year’s edition uses a slightly different primary evaluation score, and is also broader in terms of covered languages: version 1.1 of the multilingual collection of harmonized coreference resources CorefUD was used as the source of training and evaluation data this time, with 17 datasets for 12 languages. 7 systems competed in this shared task.
Authors
BibTex
@inproceedings{zabokrtsky-etal-2023-findings, title = "Findings of the Second Shared Task on Multilingual Coreference Resolution", author = "{\v{Z}}abokrtsk{\'y}, Zden{\v{e}}k and Konopik, Miloslav and Nedoluzhko, Anna and Nov{\'a}k, Michal and Ogrodniczuk, Maciej and Popel, Martin and Prazak, Ondrej and Sido, Jakub and Zeman, Daniel", editor = "{\v{Z}}abokrtsk{\'y}, Zden{\v{e}}k and Ogrodniczuk, Maciej", booktitle = "Proceedings of the CRAC 2023 Shared Task on Multilingual Coreference Resolution", month = dec, year = "2023", address = "Singapore", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2023.crac-sharedtask.1", doi = "10.18653/v1/2023.crac-sharedtask.1", pages = "1--18", abstract = "This paper summarizes the second edition of the shared task on multilingual coreference resolution, held with the CRAC 2023 workshop. Just like last year, participants of the shared task were to create trainable systems that detect mentions and group them based on identity coreference; however, this year{'}s edition uses a slightly different primary evaluation score, and is also broader in terms of covered languages: version 1.1 of the multilingual collection of harmonized coreference resources CorefUD was used as the source of training and evaluation data this time, with 17 datasets for 12 languages. 7 systems competed in this shared task.", }
