Research of applying chain conditional random fields to semantic role labeling | |
Li, Ming; Wang, Yabin; Nian, Fuzhong; Wang, Xuyang | |
2009 | |
会议日期 | November 30, 2009 - December 1, 2009 |
会议地点 | Wuhan, China |
关键词 | Feature extraction Knowledge acquisition Semantics Conditional random field Conditional Random Fields(CRFs) Long-distance dependencies Precision and recall Prepositional phrase Relationship labeling Semantic role labeling Syntactic dependency trees |
卷号 | 1 |
DOI | 10.1109/KAM.2009.210 |
页码 | 351-354 |
英文摘要 | The Conditional Random Fields (CRFs) only can deal with the sequence data of Markov property. And it can not realize the relationship labeling with more fine structure between semantic roles. An approach to semantic role labeling (SRL) based on Chain Conditional Random Fields (CCRFs) Model was proposed. The long-distance dependencies between different state variants were handled effectively via labeling Hierarchical Dependencies and Brother Dependencies of syntactic dependency tree. Moreover, some new combinative features and prepositional phrase also were added though taking advantages of any features can be added in CRFs model. The experiments were implemented on CoNLL 2008 Shared Task. The results indicate the proposed method can improve precision and recall rate of the system. © 2009 IEEE. |
会议录 | 2009 2nd International Symposium on Knowledge Acquisition and Modeling, KAM 2009
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会议录出版者 | IEEE Computer Society |
语种 | 英语 |
内容类型 | 会议论文 |
源URL | [http://ir.lut.edu.cn/handle/2XXMBERH/116697] ![]() |
专题 | 计算机与通信学院 兰州理工大学 |
作者单位 | School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China |
推荐引用方式 GB/T 7714 | Li, Ming,Wang, Yabin,Nian, Fuzhong,et al. Research of applying chain conditional random fields to semantic role labeling[C]. 见:. Wuhan, China. November 30, 2009 - December 1, 2009. |
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