Abstract
We introduce a novel parser based on a probabilistic version of a left-corner parser. The left-corner strategy is attractive because rule probabilities can be conditioned on both top-down goals and bottom-up derivations. We develop the underlying theory and explain how a grammar can be induced from analyzed data. We show that the left-corner approach provides an advantage over simple top-down probabilistic context-free grammars in parsing the Wall Street Journal using a grammar induced from the Penn Treebank. We also conclude that the Penn Treebank provides a fairly weak tes bed due to the flatness of its bracketings and to the obvious overgeneration and undergeneration of its induced grammar.- Anthology ID:
- 1997.iwpt-1.18
- 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:
- 147–158
- Language:
- URL:
- https://aclanthology.org/1997.iwpt-1.18
- DOI:
- Cite (ACL):
- Christopher D. Manning and Bob Carpenter. 1997. Probabilistic Parsing using Left Corner Language Models. In Proceedings of the Fifth International Workshop on Parsing Technologies, pages 147–158, Boston/Cambridge, Massachusetts, USA. Association for Computational Linguistics.
- Cite (Informal):
- Probabilistic Parsing using Left Corner Language Models (Manning & Carpenter, IWPT 1997)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/1997.iwpt-1.18.pdf