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A categorical analysis of coreference resolution errors in biomedical texts.

Miji Choi1, Justin Zobel2, Karin Verspoor2

  • 1Department of Computing and Information Systems, The University of Melbourne, Melbourne, Australia; National ICT Australia (NICTA), Victoria Research Laboratory, Australia.

Journal of Biomedical Informatics
|March 2, 2016
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Summary

Domain-specific coreference resolution systems outperform general systems for biomedical literature. Analysis reveals gaps in current systems, guiding future development for better information extraction.

Keywords:
Coreference resolutionError analysisNatural language processingText mining

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Area of Science:

  • Biomedical Informatics
  • Natural Language Processing
  • Information Extraction

Background:

  • Coreference resolution is crucial for extracting complex information from biomedical literature.
  • It links referring expressions to entities in biomedical events, enabling detailed participant understanding.
  • Accurate linking facilitates connecting events through shared participants.

Purpose of the Study:

  • To categorize coreference relation characteristics in the biomedical domain.
  • To compare a general coreference system's domain adaptation with domain-specific systems.
  • To develop a rule-based system for anaphoric coreference resolution.

Main Methods:

  • Categorization of coreference relations by anaphor type, syntax, and semantics.
  • Performance comparison of a general system's adaptation against domain-specific systems.
  • Development of a rule-based system using modules from existing systems.

Main Results:

  • Domain-specific systems generally outperform the adapted general system.
  • A proposed categorization enables detailed quantitative analysis of system performance.
  • Identified limitations and gaps in state-of-the-art coreference resolution systems.

Conclusions:

  • Existing coreference resolution systems for biomedical literature have coverage gaps.
  • General domain approaches require tailoring for the biomedical domain.
  • A proposed class-based error analysis framework aids in identifying system limitations and guiding future development.