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Learning Generalized Features for Semantic Role Labeling
Yang, Haitong1; Zong, Chengqing2
2016-06-01
发表期刊ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING
卷号15期号:4页码:28:1-28:16
文章类型Article
摘要This article makes an effort to improve Semantic Role Labeling (SRL) through learning generalized features. The SRL task is usually treated as a supervised problem. Therefore, a huge set of features are crucial to the performance of SKL systems. But these features often lack generalization powers when predicting an unseen argument. This article proposes a simple approach to relieve the issue. A strong intuition is that arguments occurring in similar syntactic positions are likely to bear the same semantic role, and, analogously, arguments that are lexically similar are likely to represent the same semantic role. Therefore, it will be informative to SRL if syntactic or lexical similar arguments can activate the same feature. Inspired by this, we embed the information of lexicalization and syntax into a feature vector for each argument and then use K -means to make clustering for all feature vectors of training set. For an unseen argument to be predicted, it will belong: to the same cluster as its similar arguments of training set. Therefore, the clusters can be thought of as a kind of generalized feature. We evaluate our method on several benchmarks. The experimental results show that our approach can significantly improve the SRL performance.
关键词Algorithms Languages Experimentation Performance Semantic Role Labeling Generalized Features Similar Arguments K-means
WOS标题词Science & Technology ; Technology
DOI10.1145/2890496
收录类别SCI
语种英语
项目资助者Natural Science Foundation of China(61333018) ; Strategic Priority Research Program of the CAS(XDB02070007)
WOS研究方向Computer Science
WOS类目Computer Science, Artificial Intelligence
WOS记录号WOS:000377298900008
引用统计
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/11856
专题模式识别国家重点实验室_自然语言处理
通讯作者Zong, Chengqing
作者单位1.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, Intelligence Bldg,95,Zhongguancun East Rd, Beijing 100190, Peoples R China
2.Chinese Acad Sci, Inst Automat, Natl Lab Pattern Recognit, CAS Ctr Excellence Brain Sci & Intelligence Techn, Intelligence Bldg,95,Zhongguancun East Rd, Beijing 100190, Peoples R China
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Yang, Haitong,Zong, Chengqing. Learning Generalized Features for Semantic Role Labeling[J]. ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,2016,15(4):28:1-28:16.
APA Yang, Haitong,&Zong, Chengqing.(2016).Learning Generalized Features for Semantic Role Labeling.ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING,15(4),28:1-28:16.
MLA Yang, Haitong,et al."Learning Generalized Features for Semantic Role Labeling".ACM TRANSACTIONS ON ASIAN AND LOW-RESOURCE LANGUAGE INFORMATION PROCESSING 15.4(2016):28:1-28:16.
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