基于概念结构与分布式表征的术语语义知识库构建

Construction of Terminology Semantic Knowledge Base Based on Conceptual Structure and Distributed Representation

词汇语义知识库的构建是自然语言处理中的一项基本任务,在自然语言处理的各子任务中发挥着重要作用。文章面向领域内复合型术语,提出术语概念KDML表示的自动生成方法,该方法基于概念的层级结构,采用分布式表征方法表征概念与术语定义文本,根据二者间语义距离大小进行概念消歧,通过K近邻算法学习概念间的语义角色,按照KDML语法规则生成术语概念的完整表示。实验取得首义原精确率为96%,总义原、总语义角色与总三元组的F 1值分别为91.92%、78.9%、73.41%的结果。

The construction of lexical semantic knowledge base is a basic task in natural language processing and plays an important role in various subtasks of natural language processing.This paper proposes an automatic generation method of term concept KDML representation for compound terms.The method is based on the hierarchical structure of concepts,uses distributed representation method to represent concepts and term definition text,and performs concept disambiguation according to the semantic distance between concepts and terms definition text.The method can learn the semantic roles between concepts through K-nearest neighbor algorithm,and generates term concept representation according to KDML syntax rules.Our experimental results showed that the accuracy rate of the first sememe was 96%,and the F 1 values of the total sememe,semantic role and total triple were 91.92%,78.9%and 73.41%respectively.