Towards Semi-Automatic Methods for improving WordNet

Research output: Contribution to book/anthology/report/proceedingArticle in proceedingsResearchpeer-review

  • Nervo Verdezoto, Denmark
  • Laure Vieu, IRIT-CNRS, Toulouse & LOA-ISTC-CNR, Trento, Italy
WordNet is extensively used as a major lexical resource in NLP. However, its quality is far from perfect, and this alters the results of applications using it. We propose here to complement previous efforts for “cleaning up” the top-level of its taxonomy with semi-automatic methods based on the detection of errors at the lower levels. The methods we propose test the coherence of two sources of knowledge, exploiting ontological principles and semantic constraints.
Original languageEnglish
Title of host publicationProceedings of the Ninth International Conference on Computational Semantics IWCS
Number of pages10
Place of publicationOxford, United Kingdom
PublisherThe Association for Computational Linguistics
Publication year2011
Pages275-284
DOIs
Publication statusPublished - 2011
Externally publishedYes

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