Efficacy of beam thresholding, unification filtering and hybrid parsing in probabilistic HPSG parsing

Authors:
Takashi Ninomiya;Yoshimasa Tsuruoka;Yusuke Miyao;Jun'ichi Tsujii
Affiliations:
The University of Tokyo;The University of Tokyo;The University of Tokyo;The University of Tokyo and University of Manchester and CREST, JST
Venue:
Parsing '05 Proceedings of the Ninth International Workshop on Parsing Technology
Year:
2005

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Abstract

We investigated the performance efficacy of beam search parsing and deep parsing techniques in probabilistic HPSG parsing using the Penn treebank. We first tested the beam thresholding and iterative parsing developed for PCFG parsing with an HPSG. Next, we tested three techniques originally developed for deep parsing: quick check, large constituent inhibition, and hybrid parsing with a CFG chunk parser. The contributions of the large constituent inhibition and global thresholding were not significant, while the quick check and chunk parser greatly contributed to total parsing performance. The precision, recall and average parsing time for the Penn treebank (Section 23) were 87.85%, 86.85%, and 360 ms, respectively.