Semantically significant patterns in dictionary definitions

Natural language processing systems need large lexicons containing explicit information about lexical-semantic relationships, selection restrictions, and verb categories. Because the labor involved in constructing such lexicons by hand is overwhelming, we have been trying to construct lexical entries automatically from information available in the machine-readable version of Webster's Seventh Collegiate Dictionary. This work is rich in implicit information; the problem is to make it explicit. This paper describes methods for finding taxonomy and set-membership relationships, recognizing nouns that ordinarily represent human beings, and identifying active and stative verbs and adjectives.