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Using WordNet to Extend FrameNet Coverage

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Author

Editor

  • Pierre Nugues
  • Richard Johansson

Summary, in English

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.

Publishing year

2007

Language

English

Pages

27-30

Publication/Series

LU-CS-TR: 2007-240

Document type

Conference paper

Publisher

Department of Computer Science, Lund University

Topic

  • Computer Science

Keywords

  • Frame semantics
  • natural language processing
  • WordNet
  • FrameNet

Conference name

Building Frame Semantics Resources for Scandinavian and Baltic Languages

Conference date

2007-05-24

Conference place

Tartu, Estonia

Status

Published

ISBN/ISSN/Other

  • ISBN: 978-91-976939-0-5