@inproceedings{unui-etal-1997-new,
title = "A New Formalization of Probabilistic {GLR} Parsing",
author = "Unui, Kentaro and
Sornlertlamvanich, Virach and
Tanaka, Hozumi and
Tokunaga, Takenobu",
booktitle = "Proceedings of the Fifth International Workshop on Parsing Technologies",
month = sep # " 17-20",
year = "1997",
address = "Boston/Cambridge, Massachusetts, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/1997.iwpt-1.16",
pages = "123--134",
abstract = "This paper presents a new formalization of probabilistic GLR language modeling for statistical parsing. Our model inherits its essential features from Briscoe and Carroll{'}s generalized probabilistic LR model, which obtains context-sensitivity by assigning a probability to each LR parsing action according to its left and right context. Briscoe and Carroll{'}s model, however, has a drawback in that it is not formalized in any probabilistically well-founded way, which may degrade its parsing performance. Our formulation overcomes this drawback with a few significant refinements, while maintaining all the advantages of Briscoe and Carroll{'}s modeling.",
}
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%0 Conference Proceedings
%T A New Formalization of Probabilistic GLR Parsing
%A Unui, Kentaro
%A Sornlertlamvanich, Virach
%A Tanaka, Hozumi
%A Tokunaga, Takenobu
%S Proceedings of the Fifth International Workshop on Parsing Technologies
%D 1997
%8 sep" 17 20"
%I Association for Computational Linguistics
%C Boston/Cambridge, Massachusetts, USA
%F unui-etal-1997-new
%X This paper presents a new formalization of probabilistic GLR language modeling for statistical parsing. Our model inherits its essential features from Briscoe and Carroll’s generalized probabilistic LR model, which obtains context-sensitivity by assigning a probability to each LR parsing action according to its left and right context. Briscoe and Carroll’s model, however, has a drawback in that it is not formalized in any probabilistically well-founded way, which may degrade its parsing performance. Our formulation overcomes this drawback with a few significant refinements, while maintaining all the advantages of Briscoe and Carroll’s modeling.
%U https://aclanthology.org/1997.iwpt-1.16
%P 123-134
Markdown (Informal)
[A New Formalization of Probabilistic GLR Parsing](https://aclanthology.org/1997.iwpt-1.16) (Unui et al., IWPT 1997)
ACL
- Kentaro Unui, Virach Sornlertlamvanich, Hozumi Tanaka, and Takenobu Tokunaga. 1997. A New Formalization of Probabilistic GLR Parsing. In Proceedings of the Fifth International Workshop on Parsing Technologies, pages 123–134, Boston/Cambridge, Massachusetts, USA. Association for Computational Linguistics.