A New Formalization of Probabilistic GLR Parsing
Kentaro Unui, Virach Sornlertlamvanich, Hozumi Tanaka, Takenobu Tokunaga
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.- Anthology ID:
- 1997.iwpt-1.16
- Volume:
- Proceedings of the Fifth International Workshop on Parsing Technologies
- Month:
- September 17-20
- Year:
- 1997
- Address:
- Boston/Cambridge, Massachusetts, USA
- Editors:
- Anton Nijholt, Robert C. Berwick, Harry C. Bunt, Bob Carpenter, Eva Hajicova, Mark Johnson, Aravind Joshi, Ronald Kaplan, Martin Kay, Bernard Lang, Alon Lavie, Makoto Nagao, Mark Steedman, Masaru Tomita, K. Vijay-Shanker, David Weir, Kent Wittenburg, Mats Wiren
- Venue:
- IWPT
- SIG:
- SIGPARSE
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 123–134
- Language:
- URL:
- https://aclanthology.org/1997.iwpt-1.16
- DOI:
- Bibkey:
- Cite (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.
- Cite (Informal):
- A New Formalization of Probabilistic GLR Parsing (Unui et al., IWPT 1997)
- Copy Citation:
- PDF:
- https://aclanthology.org/1997.iwpt-1.16.pdf
Export citation
@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",
editor = "Nijholt, Anton and
Berwick, Robert C. and
Bunt, Harry C. and
Carpenter, Bob and
Hajicova, Eva and
Johnson, Mark and
Joshi, Aravind and
Kaplan, Ronald and
Kay, Martin and
Lang, Bernard and
Lavie, Alon and
Nagao, Makoto and
Steedman, Mark and
Tomita, Masaru and
Vijay-Shanker, K. and
Weir, David and
Wittenburg, Kent and
Wiren, Mats",
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 %Y Nijholt, Anton %Y Berwick, Robert C. %Y Bunt, Harry C. %Y Carpenter, Bob %Y Hajicova, Eva %Y Johnson, Mark %Y Joshi, Aravind %Y Kaplan, Ronald %Y Kay, Martin %Y Lang, Bernard %Y Lavie, Alon %Y Nagao, Makoto %Y Steedman, Mark %Y Tomita, Masaru %Y Vijay-Shanker, K. %Y Weir, David %Y Wittenburg, Kent %Y Wiren, Mats %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)
- A New Formalization of Probabilistic GLR Parsing (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.