CASIA OpenIR  > 模式识别国家重点实验室  > 自然语言处理
A Global Generative Model for Chinese Semantic Role Labeling
Yang HT(杨海彤); Zong, Chengqing
2014
Conference NameProceedings of The 3rd CCF Conference on Natural Language Processing & Chinese Computing
Source PublicationProceedings of The 3rd CCF Conference on Natural Language Processing & Chinese Computing
Conference Date2014-11
Conference PlaceShen Zhen
Abstract
The predicate and its semantic roles compose a unified entity that conveys the semantics of a given sentence. A standard pipeline of current approaches to semantic role labeling (SRL) is that for a given predicate in a sentence, we can extract features for each candidate argument and then perform the role classification through a classifier. However, this process totally ignores the integrality of the predicate and its semantic roles. To address this problem, we present a global generative model in which a novel concept called Predicate-Arguments-Coalition (PAC) is proposed to encode the relations among individual arguments. Owing to PAC, our model can effectively mine the inherent properties of predicates and obtain a globally consistent solution for SRL. We conduct experiments on the standard benchmarks: Chinese PropBank. Experimental results on a single syntactic tree show that our model outperforms the state-of-the-art methods.
KeywordGlobal Generative Model
Document Type会议论文
Identifierhttp://ir.ia.ac.cn/handle/173211/11860
Collection模式识别国家重点实验室_自然语言处理
Corresponding AuthorZong, Chengqing
Recommended Citation
GB/T 7714
Yang HT,Zong, Chengqing. A Global Generative Model for Chinese Semantic Role Labeling[C],2014.
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