Using LSA and noun coordination information to improve the precision and recall of automatic hyponymy extraction

  • Authors:

  • Scott Cederberg;Dominic Widdows

  • Affiliations:

  • Stanford University, Stanford CA;Stanford University, Stanford CA

  • Venue:
  • CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
  • Year:
  • 2003

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Abstract

In this paper we demonstrate methods of improving both the recall and the precision of automatic methods for extraction of hyponymy (IS_A) relations from free text. By applying latent semantic analysis (LSA) to filter extracted hyponymy relations we reduce the rate of error of our initial pattern-based hyponymy extraction by 30%, achieving precision of 58%. Applying a graph-based model of noun-noun similarity learned automatically from coordination patterns to previously extracted correct hyponymy relations, we achieve roughly a five-fold increase in the number of correct hyponymy relations extracted.