Use of rich linguistic information to translate prepositions and grammar cases to Basque

This paper presents three successful tech-niques to translate prepositions heading verbal complements by means of rich lin-guistic information, in the context of a rule-based Machine Translation system for an agglutinative language with scarce re-sources. This information comes in the form of lexicalized syntactic dependency triples, verb subcategorization and manu-ally coded selection rules based on lex-ical, syntactic and semantic information. The first two resources have been auto-matically extracted from monolingual cor-pora. The results obtained using a new evaluation methodology show that all pro-posed techniques improve precision over the baselines, including a translation dic-tionary compiled from an aligned corpus, and a state-of-the-art statistical Machine Translation system. The results also show that linguistic information in all three tech-niques are complementary, and that a com-bination of them obtains the best F-score results overall.