Selection of Dictionary Entries from Translation Equivalents for Acquisition of Lexical Knowledge from Bilingual Corpora

Abstract

This paper points out that constructing a bilingual dictionary using translation equivalents obtained from bilingual corpora needs not only correct alignment of two expressions but also judgment of its appropriateness as an entry, and addresses the latter task which has been paid little attention. We show a method of selecting a suitable entry using Support Vector Machines, and propose to define the features by the common and the different parts between a current translation and a new translation. We examined how the selection performances are affected by the four ways of representing the common and the different parts: characters, morphemes, parts of speech, and semantic markers. Our experimental result found that representation by characters marked the best performance, F-measure of 0.837.