Coreference Resolution for the Biomedical Domain: A Survey
This work provides a comprehensive review for researchers and practitioners in biomedical NLP, focusing on incremental advancements in a domain-specific area.
The paper surveys the state-of-the-art in coreference resolution for the biomedical domain, highlighting recent developments in datasets, domain-specific language models, and architectures to address challenges in information extraction from biomedical literature.
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.