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机构地区:[1]湖北文理学院文学院,湖北襄阳441053 [2]武汉大学计算机学院,湖北武汉430072
出 处:《中文信息学报》2012年第3期22-26,32,共6页Journal of Chinese Information Processing
基 金:国家自然科学基金资助项目(90820005;61070082;61070243)
摘 要:建构大规模的汉语语义资源,是当前中文信息处理的重要任务之一。但是其中语义分析的传统方法存在一些问题,不能很好的反映汉语中各个词语或成分之间的语义关联。该文提出了基于特征结构的语义标注方法,并在此基础上建构了一个大规模的汉语语义资源。以汉语主谓谓语句为例,探讨了特征结构的标注方法。结果表明,特征结构分析解决了以往传统标注方法对汉语特殊句型无法表示的难题,包含更多的语义信息,其标注效率更高,标注精度也更高。Constructing large scale Chinese semantic resources is one of the major tasks in current Chinese Information Processing.However,the conventional approaches in semantic parsing have some defects in that they cannot denote the semantic relatedness between Chinese words and constituents.We propose a semantic annotation approach based on Feature Structure and accordingly construct large scale Chinese semantic resources.We choose "subject-predicate predicate sentence" as the research target in the paper,summarize seven categories of Feature Triples,and compare the results of three different analysis methods.Parsing based on Feature Structure solves the problems of appropriate ways to tackle the special Chinese sentence patterns.It also provides more semantic information than conventional approaches,and produces an improved annotating efficiency and accuracy.
分 类 号:TP391[自动化与计算机技术—计算机应用技术]
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