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Classification-Based Filtering of Semantic Relatedness in Hypernymy Extraction

  • Maciej Piasecki
  • Stanisław Szpakowicz
  • Michał Marcińczuk
  • Bartosz Broda
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5221)

Abstract

Manual construction of a wordnet can be facilitated by a system that suggests semantic relations acquired from corpora. Such systems tend to produce many wrong suggestions. We propose a method of filtering a raw list of noun pairs potentially linked by hypernymy, and test it on Polish. The method aims for good recall and sufficient precision. The classifiers work with complex features that give clues on the relation between the nouns. We apply a corpus-based measure of semantic relatedness enhanced with a Rank Weight Function. The evaluation is based on the data in Polish WordNet. The results compare favourably with similar methods applied to English, despite the small size of Polish WordNet.

Keywords

lexical-semantic relations measures of semantic relatedness wordnet construction Polish WordNet nouns hypernymy extraction supervised Machine Learning classifiers Rank Weight Function filtering 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Maciej Piasecki
    • 1
  • Stanisław Szpakowicz
    • 2
    • 3
  • Michał Marcińczuk
    • 1
  • Bartosz Broda
    • 1
  1. 1.Institute of Applied InformaticsWrocław University of TechnologyPoland
  2. 2.School of Information Technology and EngineeringUniversity of OttawaCanada
  3. 3.Institute of Computer SciencePolish Academy of SciencesCanada

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