Paper: Semantic Dependency Parsing using N-best Semantic Role Sequences and Roleset Information

ACL ID W08-2133
Title Semantic Dependency Parsing using N-best Semantic Role Sequences and Roleset Information
Venue International Conference on Computational Natural Language Learning
Session Main Conference
Year 2008
Authors

In this paper, we describe a syntactic and semantic dependency parsing system sub- mitted to the shared task of CoNLL 2008. The proposed system consists of five mod- ules: syntactic dependency parser, predi- cate identifier, local semantic role labeler, global role sequence candidate generator, and role sequence selector. The syntac- tic dependency parser is based on Malt Parser and the sequence candidate gen- erator is based on CKY style algorithm. The remaining three modules are imple- mented by using maximum entropy classi- fiers. The proposed system achieves 76.90 of labeled F1 for the overall task, 84.82 of labeled attachment, and 68.71 of labeled F1 on the WSJ+Brown test set.