The method outlined in this paper demonstrates that the information-theoretic similarity measure and noun-predicate bigrams are effective methods for creating lists of semantically-related words for lexical database work. Our experiments revealed that instead of serious syntactic analysis, bigrams and morpho-syntactic information sufficed for the feature-based similarity measure. We contend that our method would be even more appreciated if it applied to a raw newswire corpus in which unlisted words in existing dictionaries, such as recently-created words, proper nouns, and syllabic abbreviations, are prevailing.