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Computer Science > Computation and Language

arXiv:2109.12424 (cs)
[Submitted on 25 Sep 2021]

Title:Coreference Resolution for the Biomedical Domain: A Survey

Authors:Pengcheng Lu, Massimo Poesio
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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.
Comments: accepted at CRAC2021@EMNLP2021
Subjects: Computation and Language (cs.CL); Machine Learning (cs.LG)
Cite as: arXiv:2109.12424 [cs.CL]
  (or arXiv:2109.12424v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.2109.12424

Submission history

From: Pengcheng Lu [view email]
[v1] Sat, 25 Sep 2021 19:09:47 UTC (79 KB)
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