Integrate Statistical Model and Lexical Knowledge for Chinese Multiword Chunking

摘要：

Multiword chunking is designed as a shallow parsing technique to recognize external constituent and internal relation tags of a chunk in sentence. In this paper, we propose a new solution to deal with this problem. We design a new relation tagging scheme to represent different intra-chunk relations and make several experiments of feature engineering to select a best baseline statistical model. We also apply outside knowledge from a large-scale lexical relationship knowledge base to improve parsing performance. By integrating all above techniques, we develop a new Chinese MWC parser. Experimental results show its parsing performance can greatly exceed the rule-based parser trained and tested in the same data set.

关键词： Multiword chunking Relation tagging scheme Outside lexical knowledge base Partial parsing

作者: Qiang Zhou Hang Yu

作者单位: Centre for Speech and Language Technologies Division of TechInnovation and Dev.Tsinghua National Lab Centre for Speech and Language Technologies Division of Tech.Innovation and Dev.Tsinghua National La

会议类型: 国际会议

会议名称: The 2008 IEEE International Conference on Natural Language Processing and Knowledge Engineering(IEEE NLP-KE 2008)(2008IEEE自然语言处理与知识工程国际会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-19（万方平台首次上网日期，不代表论文的发表时间）