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 betwe...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 de- pendency 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 in- formation 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
It is difficult to analyze semantic relations automatically, especially the semantic relations of Chinese special sentence patterns. In this paper, we apply a novel model feature structure to represent Chinese semanti...It is difficult to analyze semantic relations automatically, especially the semantic relations of Chinese special sentence patterns. In this paper, we apply a novel model feature structure to represent Chinese semantic relations, which is formalized as ＂recursive directed graph＂. We focus on Chinese special sentence patterns, including the complex noun phrase, verb-complement structure, pivotal sentences, serial verb sentence and subject-predicate predicate sentence. Feature structure facilitates a richer Chinese semantic information extraction when compared with dependency structure. The results show that using recursive directed graph is more suitable for extracting Chinese complex semantic relations.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 de- pendency 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 in- formation 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.
基金Supported by the National Natural Science Foundation of China(61202193,61202304)the Major Projects of Chinese National Social Science Foundation(11&ZD189)+2 种基金the Chinese Postdoctoral Science Foundation(2013M540593,2014T70722)the Accomplishments of Listed Subjects in Hubei Prime Subject Developmentthe Open Foundation of Shandong Key Lab of Language Resource Development and Application
文摘It is difficult to analyze semantic relations automatically, especially the semantic relations of Chinese special sentence patterns. In this paper, we apply a novel model feature structure to represent Chinese semantic relations, which is formalized as ＂recursive directed graph＂. We focus on Chinese special sentence patterns, including the complex noun phrase, verb-complement structure, pivotal sentences, serial verb sentence and subject-predicate predicate sentence. Feature structure facilitates a richer Chinese semantic information extraction when compared with dependency structure. The results show that using recursive directed graph is more suitable for extracting Chinese complex semantic relations.
