An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet

  • Authors:
  • Satanjeev Banerjee;Ted Pedersen

  • Affiliations:
  • -;-

  • Venue:
  • CICLing '02 Proceedings of the Third International Conference on Computational Linguistics and Intelligent Text Processing
  • Year:
  • 2002

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Abstract

This paper presents an adaptation of Lesk's dictionary-based word sense disambiguation algorithm. Rather than using a standard dictionary as the source of glosses for our approach, the lexical database WordNet is employed. This provides a rich hierarchy of semantic relations that our algorithm can exploit. This method is evaluated using the English lexical sample data from the SENSEVAL-2 word sense disambiguation exercise, and attains an overall accuracy of 32%. This represents a significant improvement over the 16% and 23% accuracy attained by variations of the Lesk algorithm used as benchmarks during the Senseval-2 comparative exercise among word sense disambiguation systems.