指代是自然语言中一种常见的语言现象,对简化语言,减少冗余有很大的作用。指代消解是用计算机找出这些指代现象的一个过程。近几年英文指代消解研究取得了很大的成就,然而,中文指代消解研究目前还较少,一方面是由于中文自然语言处理的研究起步较晚,相关的知识较少,另外一方面就是中文相关的语料库较少,目前已知的仅有ACE2005,OntoNotes等。为了探讨语料库对中文名词短语指代消解的影响,该文实现了一个基于有监督学习方法的中文名词短语指代消解平台和一个基于无监督聚类方法的中文名词短语指代消解平台,在此平台的基础上从语料库的数量和质量两个方面来探讨语料对中文名词短语指代消解的影响。
Coreference is a common phenomenon in natural language, with a great effect in making the natural lan- guage clear and explicit illusions. Coreference resolution is the process to detect these phenomena by the computer. A great deal of research has been conducted on this task in English with substantial achievements in recent years. However, much less work has been done in this area in Chinese. One problem is the lack of public Chinese corpus for this research in except for ACE2005, OntoNotes and so on. To discuss the effect of the corpus to the Chinese Noun Phrase Anaphora Resolution, we present a Chinese noun phrase coreference resolution system that based on supervised learning approach and another system that based on unsupervised clustering approach. We discussed the effect of the corpus to the Chinese noun phrase coreference resolution based on the two platforms from the quantity and the quality of the corpus.