Building accurate semantic taxonomies from monolingual MRDs

  • Authors:
  • German Rigau;Horacio Rodríguez;Eneko Agirre

  • Affiliations:
  • Universitat Politècnica de Catalunya, Barcelona, Catalonia;Universitat Politècnica de Catalunya, Barcelona, Catalonia;Euskal Erriko Universitatea, Donostia, Basque Country

  • Venue:
  • COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
  • Year:
  • 1998

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Abstract

This paper presents a method that conbines a set of unsupervised algorithms in order to accurately build large taxonomies from any machine-readable dictionary (MRD). Our aim is to profit from conventional MRDs, with no explicit semantic coding. We propose a system that 1) performs fully automatic extraction of taxonomic links from MRD entries and 2) ranks the extracted relations in a way that selective manual refinement is allowed. Tested accuracy can reach around 100% depending on the degree of coverage selected, showing that taxonomy building is not limited to structured dictionaries such as LDOCE.