Semantic role labeling using support vector machines

Authors:
Tomohiro Mitsumori;Masaki Murata;Yasushi Fukuda;Kouichi Doi;Hirohumi Doi
Affiliations:
Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan;National Institute of Information and Communications Technology, Seika-cho, Soraku-gun, Kyoto, Japan;Sony-Kihara Research Center Inc., Shinagawa-ku, Tokyo, Japan;Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan;Nara Institute of Science and Technology, Ikoma-shi, Nara, Japan
Venue:
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Year:
2005

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Abstract

In this paper, we describe our systems for the CoNLL-2005 shared task. The aim of the task is semantic role labeling using a machine-learning algorithm. We apply the Support Vector Machines to the task. We added new features based on full parses and manually categorized words. We also report on system performance and what effect the newly added features had.