Coreference Resolution for the Biomedical Domain: A Survey

Pengcheng Lu, Massimo Poesio


Abstract
Issues with coreference resolution are one of the most frequently mentioned challenges for information extraction from the biomedical literature. Thus, the biomedical genre has long been the second most researched genre for coreference resolution after the news domain, and the subject of a great deal of research for NLP in general. In recent years this interest has grown enormously leading to the development of a number of substantial datasets, of domain-specific contextual language models, and of several architectures. In this paper we review the state of-the-art of coreference in the biomedical domain with a particular attention on these most recent developments.
Anthology ID:
2021.crac-1.2
Volume:
Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Venues:
CRAC | EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
12–23
Language:
URL:
https://aclanthology.org/2021.crac-1.2
DOI:
10.18653/v1/2021.crac-1.2
Bibkey:
Cite (ACL):
Pengcheng Lu and Massimo Poesio. 2021. Coreference Resolution for the Biomedical Domain: A Survey. In Proceedings of the Fourth Workshop on Computational Models of Reference, Anaphora and Coreference, pages 12–23, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Coreference Resolution for the Biomedical Domain: A Survey (Lu & Poesio, CRAC 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.crac-1.2.pdf
Data
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