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We use a maximum likelihood criterion to train a log-linear block bigram model which uses real-valued features -LRB- e.g. a language model score -RRB- as well as binary features based on the block identities themselves , e.g. block bigram features .
 maximum likelihood criterion, log-linear block bigram model; real-valued features, log-linear block bigram model; real-valued features, binary features; language model score, real-valued features; binary features, log-linear block bigram model
Please list all entity pairs containing a certain relationship in the given options.Output format is "word1, word2; word3, word4". 
Option: conjunction, feature of, hyponym of, used for, part of, compare, evaluate for 
Text: {0} 
Answer:
 maximum likelihood criterion, log-linear block bigram model; real-valued features, log-linear block bigram model; real-valued features, binary features; language model score, real-valued features; binary features, log-linear block bigram model