Paper: Constituency to Dependency Translation with Forests

ACL ID P10-1145
Title Constituency to Dependency Translation with Forests
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

Tree-to-string systems (and their forest- based extensions) have gained steady pop- ularity thanks to their simplicity and effi- ciency, but there is a major limitation: they are unable to guarantee the grammatical- ity of the output, which is explicitly mod- eled in string-to-tree systems via target- side syntax. We thus propose to com- bine the advantages of both, and present a novel constituency-to-dependency trans- lation model, which uses constituency forests on the source side to direct the translation, and dependency trees on the target side (as a language model) to en- sure grammaticality. Medium-scale exper- iments show an absolute and statistically significant improvement of +0.7 BLEU points over a state-of-the-art forest-based tree-to-string system even with fewer rules. This is...