From Part of Speech Tagging to Memory-based Deep Syntactic Analysis

Emmanuel Giguet, Jacques Vergne


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
Venues:
IWPT | WS
SIG:
SIGPARSE
Publisher:
Association for Computational Linguistics
Note:
Pages:
77–88
Language:
URL:
https://www.aclweb.org/anthology/1997.iwpt-1.12
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/1997.iwpt-1.12.pdf