Automatic extraction of systematic polysemy using tree-cut

  • Authors:

  • Noriko Tomuro

  • Affiliations:

  • DePaul University, Chicago, IL

  • Venue:
  • NLPComplexity '00 NAACL-ANLP 2000 Workshop: Syntactic and Semantic Complexity in Natural Language Processing Systems
  • Year:
  • 2000

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Abstract

This paper describes an automatic method for extracting systematic polysemy from a hierarchically organized semantic lexicon (WordNet). Systematic polysemy is a set of word senses that are related in systematic and predictable ways. Our method uses a modification of a tree generalization technique used in (Li and Abe, 1998), and generates a tree-cut, which is a list of clusters that partition a tree. We compare the systematic relations extracted by our automatic method to manually extracted WordNet cousins.