Statistical Models for Unsupervised Prepositional Phrase Attachment

Details Statistical Models for Unsupervised Prepositional Phrase Attachment Statistical Models for Unsupervised Prepositional Phrase Attachment

1998-07-22

arxiv.org/abs/cmp-lg/9807011v1

Proceedings of the 17th International Conference on Computational Linguistics (COLING-ACL '98)

Computer Science

Computation and Language

uses colacl.sty

Scientific paper

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 algorithms proposed for this task. We present results for prepositional phrase attachment in both English and Spanish.

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