Multilingual Dependency Learning: Exploiting Rich Features for Tagging Syntactic and Semantic Dependencies

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.

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