Paper: Three Generative Lexicalized Models For Statistical Parsing

ACL ID P97-1003
Title Three Generative Lexicalized Models For Statistical Parsing
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1997
Authors

In this paper we first propose a new sta- tistical parsing model, which is a genera- tive model of lexicalised context-free gram- mar. We then extend the model to in- clude a probabilistic treatment of both sub- categorisation and wh-movement. Results on Wall Street Journal text show that the parser performs at 88.1/87.5% constituent precision/recall, an average improvement of 2.3% over (Collins 96).