A cascaded syntactic and semantic dependency parsing system

Authors:
Wanxiang Che;Zhenghua Li;Yuxuan Hu;Yongqiang Li;Bing Qin;Ting Liu;Sheng Li
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;Harbin Institute of Technology, China
Venue:
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Year:
2008

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Abstract

We describe our CoNLL 2008 Shared Task system in this paper. The system includes two cascaded components: a syntactic and a semantic dependency parsers. A first-order projective MSTParser is used as our syntactic dependency parser. In order to overcome the shortcoming of the MSTParser, that it cannot model more global information, we add a relabeling stage after the parsing to distinguish some confusable labels, such as ADV, TMP, and LOC. Besides adding a predicate identification and a classification stages, our semantic dependency parsing simplifies the traditional four stages semantic role labeling into two: a maximum entropy based argument classification and an ILP-based post inference. Finally, we gain the overall labeled macro F1 = 82.66, which ranked the second position in the closed challenge.