中文摘要：

在真实语言环境中，词语间的联系普遍存在、错综复杂。为了更好融合和使用各种语义资源库中的语义关系，构建可计算的汉语词汇语义资源，该文提出了通过构建语义关系图整合各种语义资源的方法，并在《知网》上实现。《知网》作为一个知识库系统，对各个词语义项是以分条记录的形式存储的，各种词汇语义关系隐含在词典文件和义原描述文件中。为提取《知网》中语义间的关系，本文首先将《知网》中的概念以概念树的形式重新表示，并从概念树中提取适当的语义关系，构建语义关系图。经过处理，得到88种589984条语义关系，图上各种节点具有广泛的联系，为基于语义关系图的进一步分析和计算打下了基础。

英文摘要：

The semantic relationship between words and concepts is very common and complex in natural language. In order to effectively integrate different lexical resources and construct a computable Chinese lexical resource, we propose an automatic construction method of lexical semantic relationship graph and apply it on HowNet. As a system of knowledge, HowNet records each concept by entries, and the semantic relationship is hidden between the entries. In order to extract the relationship between the concepts in HowNet, we first re-structure the concept entries into concept trees, and then extract the semantic relationship from concept trees and construct a lexical semantic relationship graph. Finally we get 589984 relations in 88 different kinds, with rich connections between the nodes in the graph. The work in this paper provides a solid foundation for the real text content computation based on lexical semantic relationships.