Multilingual dependency-based syntactic and semantic parsing

Authors:
Wanxiang Che;Zhenghua Li;Yongqiang Li;Yuhang Guo;Bing Qin;Ting Liu
Affiliations:
Harbin Institute of Technology, China;Harbin Institute of Technology, China;Harbin Institute of Technology, China;Harbin Institute of Technology, China;Harbin Institute of Technology, China;Harbin Institute of Technology, China
Venue:
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning: Shared Task
Year:
2009

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Abstract

Our CoNLL 2009 Shared Task system includes three cascaded components: syntactic parsing, predicate classification, and semantic role labeling. A pseudo-projective high-order graph-based model is used in our syntactic dependency parser. A support vector machine (SVM) model is used to classify predicate senses. Semantic role labeling is achieved using maximum entropy (MaxEnt) model based semantic role classification and integer linear programming (ILP) based post inference. Finally, we win the first place in the joint task, including both the closed and open challenges.