基于自动模板方法的汉语语义标注

在汉语的自然语言处理领域中,汉语的语义标注一直是一个重要的研究课题。在以往的研究中,大多使用手工的方式取得模板进行标注;采用抽取自动模板的方法,对汉语的语义进行标注,以解决对词的类别进行标注,以及对复合结构语义关系进行标注的问题。实验效果表明,对词的类别进行标注取得了在把维度降到363时的精确率为81.6406%的结果;对复合结构语义关系之间的标注也取得了比以往工作有所改进的成果。

Chinese semantic labeling based on automatically extracted model

In Chinese natural language processing,semantic labeling is an important research domain.In the past researches,most label them in a manual way;in this paper,an automatically model extracting approach is applied to perform semantic labeling in Chinese,and is used to solve the problems such as classifying words and the relationships within compound nominalizations.The experiment results show that the labeling of word category has an accuracy of 81.640 5%,and the labeling of the relation within compound nominalization has also an improved result.