Sharing resources between free/open-source rule-based machine translation systems: Grammatical Framework and Apertium

In this paper, we describe two methods developed for sharing linguistic data between two free and open source rule based machine translation systems: Apertium, a shallow-transfer system; and Grammatical Framework (GF), which performs a deeper syntactic transfer. In the first method, we describe the conversion of lexical data from Apertium to GF, while in the second one we automatically extract Apertium shallow-transfer rules from a GF bilingual grammar. We evaluated the resulting systems in a English-Spanish translation context, and results showed the usefulness of the resource sharing and confirmed the a-priori strong and weak points of the systems involved.