基于语义与规则的有标复句层次体系研究

汉语复句层次关系分析是中文信息处理领域极具挑战性的课题之一。为解决关系词标识信息不充足所导致的复句层次关系识别准确率下降问题,挖掘了影响分句关联的形式化语义知识,在此基础上构建了小句关联体识别算法并将其应用于相应的复句层次判定规则之中,以辅助分析其层次关系;对于其余单、多重有标复句的层次识别,使用基于搭配规则的移进-归约算法;最后提出了一种语义与规则相结合的复句层次分析模型。实验结果表明,此方法在一定程度上提高了复句层次关系识别的准确率。

Marked complex sentence hierarchy analysis based on semantics and rules

Chinese complex sentence hierarchy analysis is one of the challenging topics in the field of Chinese information processing. In order to solve the accuracy decline of automatic recognition caused by inadequate relationship marks, we analyze formal semantic knowledge that affects sentence association, based on which we construct a small sentence association recognition algorithm and apply it to the hierarchy decision rules of complex sentences to help analyze the hierarchical relationship. As for the analysis of the hierarchy of single and multiple marked complex sentences, we leverage the shift-reduce algorithm based on collocation rules. Finally, we propose a marked complex sentence hierarchy analysis model, which combines semantics and rules. Experimental results show that this method enhances the accuracy of automatic identification to a certain extent.