Statistical models for unsupervised prepositional phrase attachment

  • Authors:
  • Adwait Ratnaparkhi

  • Affiliations:
  • University of Pennsylvania, Philadelphia, PA

  • Venue:
  • COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
  • Year:
  • 1998

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Abstract

We present several unsupervised statistical models for the prepositional phrase attachment task that approach the accuracy of the best supervised methods for this task. Our unsupervised approach uses a heuristic based on attachment proximity and trains from raw text that is annotated with only part-of-speech tags and morphological base forms, as opposed to attachment information. It is therefore less resource-intensive and more portable than previous corpus-based algorithm proposed for this task. We present results for prepositional phrase attachment in both English and Spanish.