An Unsupervised Model for Statistically Determining Coordinate Phrase Attachment

This paper examines the use of an unsupervised statistical model for determining the attachment of ambiguous coordinate phrases (CP) of the form n1 p n2 cc n3. The model presented here is based on [AR98], an unsupervised model for determining prepositional phrase attachment. After training on unannotated 1988 Wall Street Journal text, the model performs at 72% accuracy on a development set from sections 14 through 19 of the WSJ TreeBank [MSM93].

• Publication year

  1999

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  1999-06-20

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1034678.1034690
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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