Use of Rich Linguistic Information to Translate Prepositions and Grammatical 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.