Abstract
In previous work we introduced the idea of supertagging as a means of improving the efficiency of a lexicalized grammar parser. In this paper, we present supertagging in conjunction with a lightweight dependency analyzer as a robust and efficient partial parser. The present work is significant for two reasons. First, we have vastly improved our results; 92% accurate for supertag disambiguation using lexical information, larger training corpus and smoothing techniques. Second, we show how supertagging can be used for partial parsing and provide detailed evaluation results for detecting noun chunks, verb chunks, preposition phrase attachment and a variety of other linguistic constructions. Using supertag representation, we achieve a recall rate of 93.0% and a precision rate of 91.8% for noun chunking, improving on the best known result for noun chunking.- Anthology ID:
- 1997.iwpt-1.22
- 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:
- 187–198
- Language:
- URL:
- https://aclanthology.org/1997.iwpt-1.22
- DOI:
- Cite (ACL):
- B. Srinivas. 1997. Performance Evaluation of Supertagging for Partial Parsing. In Proceedings of the Fifth International Workshop on Parsing Technologies, pages 187–198, Boston/Cambridge, Massachusetts, USA. Association for Computational Linguistics.
- Cite (Informal):
- Performance Evaluation of Supertagging for Partial Parsing (Srinivas, IWPT 1997)
- PDF:
- https://preview.aclanthology.org/revert-3132-ingestion-checklist/1997.iwpt-1.22.pdf