Multilingual dependency learning: exploiting rich features for tagging syntactic and semantic dependencies

Authors:
Hai Zhao;Wenliang Chen;Jun'ichi Kazama;Kiyotaka Uchimoto;Kentaro Torisawa
Affiliations:
City University of Hong Kong, Kowloon, Hong Kong, China;National Institute of Information and Communications Technology, Soraku-gun, Kyoto, Japan;National Institute of Information and Communications Technology, Soraku-gun, Kyoto, Japan;National Institute of Information and Communications Technology, Soraku-gun, Kyoto, Japan;National Institute of Information and Communications Technology, Soraku-gun, Kyoto, Japan
Venue:
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Year:
2009

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Abstract

This paper describes our system about multilingual syntactic and semantic dependency parsing for our participation in the joint task of CoNLL-2009 shared tasks. Our system uses rich features and incorporates various integration technologies. The system is evaluated on in-domain and out-of-domain evaluation data of closed challenge of joint task. For in-domain evaluation, our system ranks the second for the average macro labeled F1 of all seven languages, 82.52% (only about 0.1% worse than the best system), and the first for English with macro labeled F1 87.69%. And for out-of-domain evaluation, our system also achieves the second for average score of all three languages.