Evaluating automated and manual acquisition of anaphora resolution strategies

  • Authors:
  • Chinatsu Aone;Scott William Bennett

  • Affiliations:
  • Systems Research and Applications Corporation (SRA), Arlington, VA;Systems Research and Applications Corporation (SRA), Arlington, VA

  • Venue:
  • ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
  • Year:
  • 1995

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Abstract

We describe one approach to build an automatically trainable anaphora resolution system. In this approach, we use Japanese newspaper articles tagged with discourse information as training examples for a machine learning algorithm which employs the C4.5 decision tree algorithm by Quinlan (Quinlan, 1993). Then, we evaluate and compare the results of several variants of the machine learning-based approach with those of our existing anaphora resolution system which uses manually-designed knowledge sources. Finally, we compare our algorithms with existing theories of anaphora, in particular, Japanese zero pronouns.