Noun classification from predicate-argument structures

  • Authors:
  • Donald Hindle

  • Affiliations:
  • AT&T Bell Laboratories, Murray Hill, NJ

  • Venue:
  • ACL '90 Proceedings of the 28th annual meeting on Association for Computational Linguistics
  • Year:
  • 1990

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Abstract

A method of determining the similarity of nouns on the basis of a metric derived from the distribution of subject, verb and object in a large text corpus is described. The resulting quasi-semantic classification of nouns demonstrates the plausibility of the distributional hypothesis, and has potential application to a variety of tasks, including automatic indexing, resolving nominal compounds, and determining the scope of modification.