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We describe an efficient decoder and show that using these tree-based models in combination with conventional SMT models provides a promising approach that incorporates the power of phrasal SMT with the linguistic generality available in a parser .
 conjunction: tree-based models, SMT models; used for: tree-based models, approach; used for: SMT models, approach; conjunction: phrasal SMT, linguistic generality; used for: phrasal SMT, parser; feature of: linguistic generality, parser
Given a phrase that describes the relationship between two words, extract the words and the lexical relationship between them. The output format should be "relation1: word1, word2; relation2: word3, word4". 
Option: conjunction, feature of, hyponym of, used for, part of, compare, evaluate for 
Text: {0} 
Answer:
 conjunction: tree-based models, SMT models; used for: tree-based models, approach; used for: SMT models, approach; conjunction: phrasal SMT, linguistic generality; used for: phrasal SMT, parser; feature of: linguistic generality, parser