Three Generative, Lexicalised Models for Statistical Parsing

Abstract

In this paper we first propose a new statistical parsing model, which is a genera-tive model of lexicalised context-free grammar. We then extend the model to include 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).

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