A new method is proposed for constructing the Chinese sentential semantic structure in this paper.The method adopts the features including predicates,relations between predicates and basic arguments,relations between ...A new method is proposed for constructing the Chinese sentential semantic structure in this paper.The method adopts the features including predicates,relations between predicates and basic arguments,relations between words,and case types to train the models of CRF + + and dependency parser. On the basis of the data set in Beijing Forest Studio-Chinese Tagged Corpus( BFS-CTC),the proposed method obtains precision value of 73. 63% in open test. This result shows that the formalized computer processing can construct the sentential semantic structure absolutely. The features of predicates,topic and comment extracted with the method can be applied in Chinese information processing directly for promoting the development of Chinese semantic analysis.The method makes the analysis of sentential semantic analysis based on large scale of data possible. It is a tool for expanding the corpus and has certain theoretical research and practical application value.展开更多
基金Supported by the Science and Technology Innovation Plan of Beijing Institute of Technology(2013)
文摘A new method is proposed for constructing the Chinese sentential semantic structure in this paper.The method adopts the features including predicates,relations between predicates and basic arguments,relations between words,and case types to train the models of CRF + + and dependency parser. On the basis of the data set in Beijing Forest Studio-Chinese Tagged Corpus( BFS-CTC),the proposed method obtains precision value of 73. 63% in open test. This result shows that the formalized computer processing can construct the sentential semantic structure absolutely. The features of predicates,topic and comment extracted with the method can be applied in Chinese information processing directly for promoting the development of Chinese semantic analysis.The method makes the analysis of sentential semantic analysis based on large scale of data possible. It is a tool for expanding the corpus and has certain theoretical research and practical application value.
