Filtering Machine Translation Results with Automatically Constructed Concept Lattices

Concept lattices can significantly improve machine translation systems when applied as filters to their results. We have developed a rule-based machine translator from Turkish to English in a unification-based programming paradigm and supplemented it with an automatically constructed concept lattice. The test results achieved by applying this translation system to a Turkish child story reveals that lattices used as filters to translation results have a promising potential to improve machine translation. We have compared our system with Google Translate on the data. The comparison suggests that a rulebased system can even compete with this statistical machine translation system that stands out with its wide range of users.