Abstract
This paper examines the use of an unsupervised statistical model for determining the attachment of ambiguous coordinate phrases (CP) of the form nl p n2 cc n3. The model presented here is based on JAR98], 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].
Cite
CITATION STYLE
Goldberg, M. (1999). An unsupervised model for statistically determining coordinate phrase attachment. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 1999-June, pp. 610–614). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1034678.1034690
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