Three Generative, Lexicalised Models for Statistical Parsing

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).

• Publication year

  1997

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  1997-06-17

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/976909.979620arXiv cmp-lg/9706022
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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