Unsupervised event coreference resolution with rich linguistic features

  • Authors:
  • Cosmin Adrian Bejan;Sanda Harabagiu

  • Affiliations:
  • University of Southern California, Marina del Rey, CA;University of Texas at Dallas, Richardson, TX

  • Venue:
  • ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
  • Year:
  • 2010

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Abstract

This paper examines how a new class of nonparametric Bayesian models can be effectively applied to an open-domain event coreference task. Designed with the purpose of clustering complex linguistic objects, these models consider a potentially infinite number of features and categorical outcomes. The evaluation performed for solving both within- and cross-document event coreference shows significant improvements of the models when compared against two baselines for this task.