Word Sense Acquisition from Bilingual Comparable Corpora

Manually constructing an inventory of word senses has suffered from problems including high cost, arbitrary assignment of meaning to words, and mismatch to domains. To overcome these problems, we propose a method to assign word meaning from a bilingual comparable corpus and a bilingual dictionary. It clusters second-language translation equivalents of a first-language target word on the basis of their translingually aligned distribution patterns. Thus it produces a hierarchy of corpus-relevant meanings of the target word, each of which is defined with a set of translation equivalents. The effectiveness of the method has been demonstrated through an experiment using a comparable corpus consisting of Wall Street Journal and Nihon Keizai Shimbun corpora together with the EDR bilingual dictionary.