A Thesaurus which Classifies Terms by Facets for Natural Language Processing of Japanese

Abstract

Instead of a thesaurus specialized in conventional information retrieval, we developed a thesaurus of 420,000 terms for the purpose of natural language processing such as parsing or the term standardization. Because each entry term has a large number of terms with various semantic relations, we introduce a facet and classify them for finding relative terms easily. Furthermore, we distinguish discriminatory terms, and fluctuating Japanese spellings. We described points to keep in mind and future tasks in making a thesaurus. Our package has the connecting function with the Internet and the other dictionaries.