Three Generative, Lexicalised Models for Statistical Parsing
arXiv:cmp-lg/9706022
Abstract
In this paper we first propose a new statistical parsing model, which is a generative model of lexicalised context-free grammar. We then extend the model to include a probabilistic treatment of both subcategorisation 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).
8 pages, to appear in Proceedings of ACL/EACL 97.