基于句义结构分析的中文人名消歧

针对现有很多基于人物属性特征的人名消歧方法不适用于文本本身特征稀疏的问题，提出一种基于句义结构分析中文人名消歧方法。通过句义结构分析提取人物关系特征词，根据提取关系特征构建社会关系图，并以人名实体的职业和所在单位等人物属性作为辅助特征，结合实体的特征信息进行关系聚类，将聚类的结果映射到文本中以实现人名消歧。通过句义结构分析提高了人物关系特征以及人物属性特征的准确率，实验结果表明，该方法可有效地提高中文人名消歧准确率。

Chinese name disambiguation based on analysis of sentential semantic structure

Many existing methods of name disambiguation based on human features are not suitable for documents due to their sparsity. For solving this problem, this paper proposed a human social relationship based Chinese name disambiguation by analyzing sentential semantic structure. Firstly, it built a graph of social relationships according to the characters of human social relationships. Then, it clustered the relationships by combing with the attributes of the name entity, such as his career and unit, as auxiliary characters. After name disambiguation, original documents can be summarized by the name which the documents discuss. The experimental results show that the analysis of sentential semantic structure is able to improve the precision of personal relationships and attributes,so it effectively improves the performance of name disambiguation.