Utilizing semantic equivalence classes of Japanese functional expressions in machine translation

Abstract

This paper applied "Sandglass" machine translation architecture to the task of translating Japanese functional expressions into English. We employ the semantic equivalence classes of a recently compiled large scale hierarchical lexicon of Japanese functional expressions. We examine each class whether it is monosemous or not. We realize this procedure by empirically studying whether functional expressions within a class can be translated into a single canonical English expression. Furthermore, in order to precisely identify the class of functional expressions to which our translation rule is directly applicable, we further introduce two types of ambiguities of functional expressions and identify monosemous functional expressions. We finally show that the proposed framework outperforms commercial machine translation software products.