P13-1001 algorithm for phrase-based string-to - dependency translation . As the algorithm generates
D10-1060 three examples of string-to - dependency translation rules . For the sake of con -
P13-1001 evaluated our phrase-based string-to - dependency translation system on Chinese - English translation
D13-1053 improves a strong string-to - dependency translation baseline on multiple evaluation
P13-1001 algorithm for phrase-based string-to - dependency translation . Figure 2 shows an example .
D15-1248 morphological structure jointly in a dependency translation model , allowing the system to
J00-1004 Bangalore , and Douglas Learning Dependency Translation Models nodes in the source and
N13-1002 systems . MTUs have been used in dependency translation models ( Quirk and Menezes ,
P10-1145 associated with a constituency to dependency translation rule . How - ever , pattern-matching
P10-1145 tree De , our constituency to dependency translation model can be formalized as :
P10-1145 tion , r is a constituency to dependency translation rule . 2.1 Constituency Forests
J00-1004 01 IV 701 VO . <title> Learning Dependency Translation Models as Collections of Finite-State
P13-2071 Khalilov and Fonollosa , 2009 ) , in dependency translation models ( Quirk and Menezes ,
J00-1001 languages . Finally , Learning Dependency Translation Models as Collections of Finite-State
J14-2005 . 3.2 Quasi-Synchronous Phrase Dependency Translation Let X denote the set of all strings
P10-1145 TIN2009-13391-C04-04 ) . <title> Constituency to Dependency Translation with Forests </title> Mi Liu
P10-1145 More formally , a constituency to dependency translation rule r is a tuple ( lhs ( r )
J00-1000 Context-Free Languages Learning Dependency Translation Models as Collections of Finite-State
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