Acquisition and Maintenance of Knowledge Bases for Natural Language Processing Systems

这项研究是卡内基的谢尔盖·尼伦伯格和 梅隆大学和普渡大学的维克托拉斯金。他们的目标 是推进自然科学知识库的最新发展， 语言处理 他们正在建立关于单词的知识库， 词义和词语关系，延伸到“玩具”领域之外 要足够全面的自然语言处理 现实情况。 这些“计算词典学” 知识库是自动计算机系统的基础， 分析自然语言并生成自然语言 输出. 本研究的意义在于， 自然语言处理是开发 计算机系统接口。 关于word的计算机化知识库 意义和世界知识是自然语言不可或缺的 处理系统. 这项工作开始建立框架， 这种知识库和获取其内容的工具， 这将是有用的许多研究小组和适合于 不同的应用。

This research is joint work of Sergei Nirenburg at Carnegie Mellon University and Victor Raskin at Purdue University. Their goal is to advance the state of the art in knowledge bases for natural language processing. They are building knowledge bases about words, word meanings and word relationships, extended beyond "toy" domains to be comprehensive enough for natural language processing in realistic situations. These kinds of "computational lexicography" knowledge bases are fundamental to automatic computer systems for analyzing natural language and for generating natural language output. The significance of this research is that automatic processing of natural language is a major component in developing computer systems interface. Computerized knowledge bases about word meanings and world knowledge are indispensable to natural language processing systems. This work begins to build the framework for such knowledge bases and the tools for acquiring their content, in a way which will be useful to many research groups and suitable for diverse applications.