Abstract
There are currently two philosophies for building grammars and parsers – Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.- Anthology ID:
- 1995.iwpt-1.27
- Volume:
- Proceedings of the Fourth International Workshop on Parsing Technologies
- Month:
- September 20-24
- Year:
- 1995
- Address:
- Prague and Karlovy Vary, Czech Republic
- Editors:
- Eva Hajicova, Bernard Lang, Robert Berwick, Harry Bunt, Bob Carpenter, Ken Church, Aravind Joshi, Ronald Kaplan, Martin Kay, Makoto Nagao, Anton Nijholt, Mark Steedman, Henry Thompson, Masaru Tomita, K. Vijay-Shanker, Yorick Wilks, Kent Wittenburg
- Venues:
- IWPT | WS
- SIG:
- SIGPARSE
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 224–233
- Language:
- URL:
- https://aclanthology.org/1995.iwpt-1.27
- DOI:
- Bibkey:
- Cite (ACL):
- B. Srinivas, Christine Doran, and Seth Kulick. 1995. Heuristics and Parse Ranking. In Proceedings of the Fourth International Workshop on Parsing Technologies, pages 224–233, Prague and Karlovy Vary, Czech Republic. Association for Computational Linguistics.
- Cite (Informal):
- Heuristics and Parse Ranking (Srinivas et al., IWPT-WS 1995)
- Copy Citation:
- PDF:
- https://aclanthology.org/1995.iwpt-1.27.pdf
Export citation
@inproceedings{srinivas-etal-1995-heuristics,
title = "Heuristics and Parse Ranking",
author = "Srinivas, B. and
Doran, Christine and
Kulick, Seth",
editor = "Hajicova, Eva and
Lang, Bernard and
Berwick, Robert and
Bunt, Harry and
Carpenter, Bob and
Church, Ken and
Joshi, Aravind and
Kaplan, Ronald and
Kay, Martin and
Nagao, Makoto and
Nijholt, Anton and
Steedman, Mark and
Thompson, Henry and
Tomita, Masaru and
Vijay-Shanker, K. and
Wilks, Yorick and
Wittenburg, Kent",
booktitle = "Proceedings of the Fourth International Workshop on Parsing Technologies",
month = sep # " 20-24",
year = "1995",
address = "Prague and Karlovy Vary, Czech Republic",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/1995.iwpt-1.27",
pages = "224--233",
abstract = "There are currently two philosophies for building grammars and parsers {--} Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics.",
}
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%0 Conference Proceedings %T Heuristics and Parse Ranking %A Srinivas, B. %A Doran, Christine %A Kulick, Seth %Y Hajicova, Eva %Y Lang, Bernard %Y Berwick, Robert %Y Bunt, Harry %Y Carpenter, Bob %Y Church, Ken %Y Joshi, Aravind %Y Kaplan, Ronald %Y Kay, Martin %Y Nagao, Makoto %Y Nijholt, Anton %Y Steedman, Mark %Y Thompson, Henry %Y Tomita, Masaru %Y Vijay-Shanker, K. %Y Wilks, Yorick %Y Wittenburg, Kent %S Proceedings of the Fourth International Workshop on Parsing Technologies %D 1995 %8 sep 20 24 %I Association for Computational Linguistics %C Prague and Karlovy Vary, Czech Republic %F srinivas-etal-1995-heuristics %X There are currently two philosophies for building grammars and parsers – Statistically induced grammars and Wide-coverage grammars. One way to combine the strengths of both approaches is to have a wide-coverage grammar with a heuristic component which is domain independent but whose contribution is tuned to particular domains. In this paper, we discuss a three-stage approach to disambiguation in the context of a lexicalized grammar, using a variety of domain independent heuristic techniques. We present a training algorithm which uses hand-bracketed treebank parses to set the weights of these heuristics. We compare the performance of our grammar against the performance of the IBM statistical grammar, using both untrained and trained weights for the heuristics. %U https://aclanthology.org/1995.iwpt-1.27 %P 224-233
Markdown (Informal)
[Heuristics and Parse Ranking](https://aclanthology.org/1995.iwpt-1.27) (Srinivas et al., IWPT-WS 1995)
- Heuristics and Parse Ranking (Srinivas et al., IWPT-WS 1995)
ACL
- B. Srinivas, Christine Doran, and Seth Kulick. 1995. Heuristics and Parse Ranking. In Proceedings of the Fourth International Workshop on Parsing Technologies, pages 224–233, Prague and Karlovy Vary, Czech Republic. Association for Computational Linguistics.