Anaphora resolution in biomedical literature: a hybrid approach

  • Authors:
  • Jennifer D'Souza;Vincent Ng

  • Affiliations:
  • University of Texas at Dallas, Richardson, TX;University of Texas at Dallas, Richardson, TX

  • Venue:
  • Proceedings of the ACM Conference on Bioinformatics, Computational Biology and Biomedicine
  • Year:
  • 2012

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Abstract

While traditional work on anaphora resolution has focused on resolving anaphors in newspaper and newswire articles, the surge of interest in biomedical natural language processing in recent years has stimulated work on anaphora resolution in biomedical texts. Existing anaphora resolvers, whether applied to the biomedical domain or not, have adopted either a learning-based or a rule-based approach. We hypothesize that both approaches have their unique strengths, and propose in this paper a hybrid approach to anaphora resolution in biomedical texts that aims to combine their strengths. Our hybrid approach achieves an F-score of 60.9 on the BioNLP-2011 coreference dataset, which to our knowledge is the best result reported to date on this dataset.