Can corpus pattern analysis be used in NLP?

  • Authors:
  • Silvie Cinková;Martin Holub;Pavel Rychlý;Lenka Smejkalová;Jana ýindlerová

  • Affiliations:
  • Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics;Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics;Masaryk University in Brno, Faculty of Informatics, Department of Information Technology;Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics;Charles University in Prague, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics

  • Venue:
  • TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
  • Year:
  • 2010

Quantified Score

Hi-index 0.00

Visualization

Abstract

Corpus Pattern Analysis (CPA) [1], coined and implemented by Hanks as the Pattern Dictionary of English Verbs (PDEV) [2], appears to be the only deliberate and consistent implementation of Sinclair's concept of Lexical Item [3]. In his theoretical inquiries [4] Hanks hypothesizes that the pattern repository produced by CPA can also support the word sense disambiguation task. Although more than 670 verb entries have already been compiled in PDEV, no systematic evaluation of this ambitious project has been reported yet. Assuming that the Sinclairian concept of the Lexical Item is correct, we started to closely examine PDEV with its possible NLP application in mind. Our experiments presented in this paper have been performed on a pilot sample of English verbs to provide a first reliable view on whether humans can agree in assigning PDEV patterns to verbs in a corpus. As a conclusion we suggest procedures for future development of PDEV.