GLR Parser with Conditional Action Model using Surface Phrasal Types for Korean

Yong-Jae Kwak, So-Young Park, Hae-Chang Rim


Abstract
In this paper, we propose a new probabilistic GLR parsing method that can solve the problems of conventional methods. Our proposed Conditional Action Model uses Surface Phrasal Types (SPTs) encoding the functional word sequences of the sub-trees for describing structural characteristics of the partial parse. And, the proposed GLR model outperforms the previous methods by about 6~8%.
Anthology ID:
W03-3013
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:
213–214
Language:
URL:
https://www.aclweb.org/anthology/W03-3013
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/W03-3013.pdf