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

ACL ID W09-1209
Title Multilingual Dependency Learning: Exploiting Rich Features for Tagging Syntactic and Semantic Dependencies
Venue International Conference on Computational Natural Language Learning
Session shared task
Year 2009
Authors

This paper describes our system about mul- tilingual 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 in- tegration technologies. The system is evalu- ated on in-domain and out-of-domain evalu- ation 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.