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Using WordNet to Extend FrameNet Coverage

Publiceringsår: 2007
Språk: Engelska
Sidor: 27-30
Publikation/Tidskrift/Serie: LU-CS-TR: 2007-240
Dokumenttyp: Konferensbidrag
Förlag: Department of Computer Science, Lund University


We present two methods to address the problem of sparsity in the FrameNet lexical database. The first method is based on the idea that a word that belongs to a frame is ``similar'' to the other words in that frame. We measure the similarity using a WordNet-based variant of the Lesk metric. The second method uses the sequence of synsets in WordNet hypernym trees as feature vectors that can be used to train a classifier to determine whether a word belongs to a frame or not. The extended dictionary produced by the second method was used in a system for FrameNet-based
semantic analysis and gave an improvement in recall.
We believe that the methods are useful for bootstrapping FrameNets for new languages.



  • Computer Science
  • Frame semantics
  • natural language processing
  • WordNet
  • FrameNet


Building Frame Semantics Resources for Scandinavian and Baltic Languages
Tartu, Estonia
  • ISBN: 978-91-976939-0-5

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