Lexical Transfer Ambiguity Resolution Using Automatically-Extracted Concept Co-occurrence Information

Abstract

This paper describes a method for lexical transfer ambiguity resolution using corpus and concept information. Previous research has restricted the use of linguistic knowledge to the lexical level. Since the extracted knowledge is stored in words themselves, these methods require a large amount of space with a low recall rate. On the contrary, we resolve word sense ambiguity by using concept co-occurrence information extracted from an automatically sense-tagged corpus. The tested accuracy of our method exceeds 82.4% for nominal words, and 83% for verbal words.