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Prepositional Phrase Reordering for Hierarchical Phrase-Based Translation

FENG Yang1,ZHANG Dongdong2,LIU Qun1(1.Key Laboratory of Intelligent Information Processing,Institute of Computing Technology, Chinese Academy of Sciences,Beijing 100190,China; 2.Microsoft Research Asia,Beijing 100190,China)  
In different languages,the relative order of syntactic constituents is usually different,especially for prepositional phrases.Therefore,to the proper treatment of the syntactic order differences is of vital importance to translation quality.Hierarchical phrase-based model learns formally syntax from a parallel corpus and is capable of dealing with long-distance reordering.But it fails in discriminating the syntactic constituents to select the correct translation rule.In this paper,we introduce linguistic information into hierarchical phrase-based model in the form of prepositional phrases so as to well capture the reordering of prepositional phrases.This method first identifies prepositional phrases via conditional random fields and extracts rules including prepositional phrases.Under the SCFG defined by these rules,it searches for the best derivation and produces translation simultaneously.Experiments show that,comparing to hierarchical phrase-based model,our method can get an absolute improvement of 0.8 BLEU point on our in-house English-Chinese test set and 0.5 BLEU point on the NIST 2008 English-Chinese test set.
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