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Three generative, lexicalised models for statistical parsing
Open accessAbstract
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).
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Marcus, M. (1993) · doi:10.21236/ada273556 · Cited by 7,405
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Metadata
- Authors
- Collins, M.
- Venue
- Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics -
- Published
- 1997
- Pages
- 16-23
- OpenAlex
- W2788296320
- Cited by
- 188
- References
- 1
- FWCI
- 7.66
- Type
- conference paper
- Language
- en
- Open access
- bronze
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- Collins, M. (1997). Three generative, lexicalised models for statistical parsing. Proceedings of the eighth conference on European chapter of the Association for Computational Linguistics -. https://doi.org/10.3115/979617.979620
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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