Word sense disambiguation: a case study on the granularity of sense distinctions

  • Authors:
  • Dan Tufis

  • Affiliations:
  • Research Institute for Artificial Intelligence, Bucharest, Romania

  • Venue:
  • ISPRA'05 Proceedings of the 4th WSEAS International Conference on Signal Processing, Robotics and Automation
  • Year:
  • 2005

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Abstract

The paper presents a method for word sense disambiguation (WSD) based on parallel corpora. The method exploits recent advances in word alignment and word clustering based on automatic extraction of translation equivalents and is supported by a lexical ontology made of aligned wordnets for the languages in the corpora. The wordnets are aligned to the Princeton Wordnet, according to the principles established by EuroWordNet. The evaluation of the WSD system was performed using three different granularity sense inventories.