Combining Rule-based and Data-driven Techniques for Grammatical Relation Extraction in Spoken Language

Kenji Sagae, Alon Lavie


Abstract
We investigate an aspect of the relationship between parsing and corpus-based methods in NLP that has received relatively little attention: coverage augmentation in rule-based parsers. In the specific task of determining grammatical relations (such as subjects and objects) in transcribed spoken language, we show that a combination of rule-based and corpus-based approaches, where a rule-based system is used as the teacher (or an automatic data annotator) to a corpus-based system, outperforms either system in isolation.
Anthology ID:
W03-3019
Volume:
Proceedings of the Eighth International Conference on Parsing Technologies
Month:
April
Year:
2003
Address:
Nancy, France
Venues:
IWPT | WS
SIG:
SIGPARSE
Publisher:
Note:
Pages:
Language:
URL:
https://www.aclweb.org/anthology/W03-3019
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W03-3019.pdf