2002 GenerativeModelsforStatisticalP

• (Hockenmaier & Steedman, 2002) ⇒ Julia Hockenmaier, and Mark Steedman. (2002). “Generative Models for Statistical Parsing with Combinatory Categorial Grammar.” In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics. doi:10.3115/1073083.1073139

Subject Headings: CCG Parser.

Cited By

• http://scholar.google.com/scholar?q=%222002%22+Generative+Models+for+Statistical+Parsing+with+Combinatory+Categorial+Grammar
• http://dl.acm.org/citation.cfm?id=1073083.1073139&preflayout=flat#citedby

Quotes

Abstract

This paper compares a number of generative probability models for a wide-coverage Combinatory Categorial Grammar (CCG) parser. These models are trained and tested on a corpus obtained by translating the Penn Treebank trees into CCG normal-form derivations. According to an evaluation of unlabeled word-word dependencies, our best model achieves a performance of 89.9%, comparable to the figures given by Collins (1999) for a linguistically less expressive grammar. In contrast to Gildea (2001), we find a significant improvement from modeling word-word dependencies.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2002 GenerativeModelsforStatisticalP	Mark Steedman Julia Hockenmaier			Generative Models for Statistical Parsing with Combinatory Categorial Grammar				10.3115/1073083.1073139		2002