Paper: An Unsupervised Model For Statistically Determining Coordinate Phrase Attachment

ACL ID P99-1081
Title An Unsupervised Model For Statistically Determining Coordinate Phrase Attachment
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1999
Authors

This paper examines the use of an unsuper- vised statistical model for determining the at- tachment of ambiguous coordinate phrases (CP) of the form nl p n2 cc n3. The model pre- sented here is based on JAR98], an unsupervised model for determining prepositional phrase at- tachment. 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].