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Classifying Functional Relations in Factotum via WordNet Hypernym Associations

  • Tom O’Hara
  • Janyce Wiebe
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2588)

Abstract

This paper describes how to automatically classify the functional relations from the Factotum knowledge base via a statistical machine learning algorithm. This incorporates a method for inferring prepositional relation indicators from corpus data. It also uses lexical collocations (i.e., word associations) and class-based collocations based on the WordNet hypernym relations (i.e., is-subset-of). The result shows substantial improvement over a baseline approach.

Keywords

Semantic Relation Machine Translation Functional Relation Semantic Network Semantic Role 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Tom O’Hara
    • 1
  • Janyce Wiebe
    • 2
  1. 1.Department of Computer ScienceNew Mexico State UniversityLas Cruces
  2. 2.Department of Computer ScienceUniversity of PittsburghPittsburgh

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