An Adapted Lesk Algorithm for Word Sense Disambiguation Using WordNet

  • Satanjeev Banerjee
  • Ted Pedersen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2276)


This paper presents an adaptation of Lesk’s dictionarybased 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.


Target Word Function Word Relation Pair Word Sense Disambiguation Context Window 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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    C. Fellbaum, editor. WordNet: An electronic lexical database. MIT Press, 1998.Google Scholar
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    M. Lesk. Automatic sense disambiguation using machine readable dictionaries: How to tell a pine cone from a ice cream cone. In Proceedings of SIGDOC’ 86, 1986.Google Scholar
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    G. Sidorov and A. Gelbukh. Word sense disambiguation in a Spanish explanatory dictionary. In Proceedings of TALN, pages 398–402, Tours, France, 2001.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Satanjeev Banerjee
    • 1
  • Ted Pedersen
    • 1
  1. 1.University of MinnesotaDuluthUSA

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