Graph-cut-based anaphoricity determination for coreference resolution

  • Authors:
  • Vincent Ng

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

  • Venue:
  • NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

Recent work has shown that explicitly identifying and filtering non-anaphoric mentions prior to coreference resolution can improve the performance of a coreference system. We present a novel approach to this task of anaphoricity determination based on graph cuts, and demonstrate its superiority to competing approaches by comparing their effectiveness in improving a learning-based coreference system on the ACE data sets.