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In this paper , we first train two statistical word alignment models with the large-scale out-of-domain corpus and the small-scale in-domain corpus respectively , and then interpolate these two models to improve the domain-specific word alignment .
 used for: large-scale out-of-domain corpus, statistical word alignment models; conjunction: large-scale out-of-domain corpus, small-scale in-domain corpus; used for: small-scale in-domain corpus, statistical word alignment models; used for: models, domain-specific word alignment
Given options, please tell me the relationships of all the listed entity pairs.Output format is "relation1: word1, word2; relation2: word3, word4". 
Option: conjunction, feature of, hyponym of, used for, part of, compare, evaluate for 
Text: {0} 
 Entity Pairs:  large-scale out-of-domain corpus, statistical word alignment models; large-scale out-of-domain corpus, small-scale in-domain corpus; small-scale in-domain corpus, statistical word alignment models; models, domain-specific word alignment 
Answer:
 used for: large-scale out-of-domain corpus, statistical word alignment models; conjunction: large-scale out-of-domain corpus, small-scale in-domain corpus; used for: small-scale in-domain corpus, statistical word alignment models; used for: models, domain-specific word alignment