A pipeline approach for syntactic and semantic dependency parsing

Authors:
Yotaro Watanabe;Masakazu Iwatate;Masayuki Asahara;Yuji Matsumoto
Affiliations:
Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan;Nara Institute of Science and Technology, Ikoma, Nara, Japan
Venue:
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Year:
2008

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Abstract

This paper describes our system for syntactic and semantic dependency parsing to participate the shared task of CoNLL-2008. We use a pipeline approach, in which syntactic dependency parsing, word sense disambiguation, and semantic role labeling are performed separately: Syntactic dependency parsing is performed by a tournament model with a support vector machine; word sense disambiguation is performed by a nearest neighbour method in a compressed feature space by probabilistic latent semantic indexing; and semantic role labeling is performed by a an online passive-aggressive algorithm. The submitted result was 79.10 macro-average F1 for the joint task, 87.18% syntactic dependencies LAS, and 70.84 semantic dependencies F1. After the deadline, we constructed the other configuration, which achieved 80.89 F1 for the joint task, and 74.53 semantic dependencies F1. The result shows that the configuration of pipeline is a crucial issue in the task.