Constituency to Dependency Translation with Forests
Haitao Mi, Qun Liu · 2010
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 also the first time that a tree-to-tree model can surpass tree-to-string counterparts. 1