A nearest-neighbor method for resolving PP-Attachment ambiguity

  • Authors:
  • Shaojun Zhao;Dekang Lin

  • Affiliations:
  • Department of Computing Science, University of Alberta, Edmonton, Alberta;Department of Computing Science, University of Alberta, Edmonton, Alberta

  • Venue:
  • IJCNLP'04 Proceedings of the First international joint conference on Natural Language Processing
  • Year:
  • 2004

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Abstract

We present a nearest-neighbor algorithm for resolving prepositional phrase attachment ambiguities. Its performance is significantly higher than previous corpus-based methods for PP-attachment that do not rely on manually constructed knowledge bases. We will also show that the PP-attachment task provides a way to evaluate methods for computing distributional word similarities. Our experiments indicate that the cosine of pointwise mutual information vector is a significantly better similarity measure than several other commonly used similarity measures.