Learning to resolve bridging references

  • Authors:
  • Massimo Poesio;Rahul Mehta;Axel Maroudas;Janet Hitzeman

  • Affiliations:
  • University of Essex, UK;University of Essex, UK;University of Essex, UK;MITRE Corporation

  • Venue:
  • ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
  • Year:
  • 2004

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Abstract

We use machine learning techniques to find the best combination of local focus and lexical distance features for identifying the anchor of mereological bridging references. We find that using first mention, utterance distance, and lexical distance computed using either Google or WordNet results in an accuracy significantly higher than obtained in previous experiments.