自然语言处理中的语义关系与句法模式互发现*

在国家科技基础条件平台中如何建设汉语字词之间的语义关系库，并且利用初始的语义关系库自动获取句法模式和新的关系。使用了句法模式的概念，并提出了利用已有关系发现新模式、利用已有模式发现新关系的方法，创造性地设计相关模型并实现了一个中文语义关系知识库系统。利用此系统结合自然语言处理相关技术，从搜狗语料库和百度百科页面文件中大规模自动化获取了有效关系200多个，并从中提取了继承、同义等有效的新关系1 000多条。实验证明其效率达到约40%，主要取决于关系中查询词的距离取值和语料库本身的性质。

Mutual extraction between semantic relationships and lexical patterns in natural language processing

This paper focused on an automatic approach to build a semantic relationship database in the national science and technology infrastructure platform, identified lexical patterns and extended new semantic relationships by existing ones from corpus. In fact there were a lot of potential relationships between words, and these words could be connected to a big network by them. So the problem was how to model this network and how to get relationships automatically. With the concept of lexical pattern, devised a new method: generalized new patterns form the existing relationships and generalized new relationships from existing patterns. This paper designed and realized a Chinese semantic relationships knowledgebase system. Using this system and NLP technology, extracted more than 200 effective relationships and more than 1 000 new relationships (such as inherit and synonym) from Sogou corpus and Baidu Baike. The experiment result shows that the precision of these relationships is around 40%, depends on the distance between the searching words and the type of articles in corpus.