Abstract
This paper presents a robust system for deep syntactic parsing of unrestricted French. This system uses techniques from Part-of-Speech tagging in order to build a constituent structure and uses other techniques from dependency grammar in an original framework of memories in order to build a functional structure. The two structures are build simultaneously by two interacting processes. The processes share the same aim, that is, to recover efficiently and reliably syntactic information with no explicit expectation on text structure.- Anthology ID:
- 1997.iwpt-1.12
- 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:
- 77–88
- Language:
- URL:
- https://aclanthology.org/1997.iwpt-1.12
- DOI:
- Cite (ACL):
- Emmanuel Giguet and Jacques Vergne. 1997. From Part of Speech Tagging to Memory-based Deep Syntactic Analysis. In Proceedings of the Fifth International Workshop on Parsing Technologies, pages 77–88, Boston/Cambridge, Massachusetts, USA. Association for Computational Linguistics.
- Cite (Informal):
- From Part of Speech Tagging to Memory-based Deep Syntactic Analysis (Giguet & Vergne, IWPT 1997)
- PDF:
- https://preview.aclanthology.org/teach-a-man-to-fish/1997.iwpt-1.12.pdf