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The information extraction system we evaluate is based on a linear-chain conditional random field -LRB- CRF -RRB- , a probabilistic model which has performed well on information extraction tasks because of its ability to capture arbitrary , overlapping features of the input in a Markov model .
 used for: linear-chain conditional random field -LRB- CRF -RRB-, information extraction system; hyponym of: linear-chain conditional random field -LRB- CRF -RRB-, probabilistic model; used for: probabilistic model, information extraction tasks; used for: probabilistic model, arbitrary , overlapping features; feature of: arbitrary , overlapping features, input; part of: arbitrary , overlapping features, Markov model
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:
 used for: linear-chain conditional random field -LRB- CRF -RRB-, information extraction system; hyponym of: linear-chain conditional random field -LRB- CRF -RRB-, probabilistic model; used for: probabilistic model, information extraction tasks; used for: probabilistic model, arbitrary , overlapping features; feature of: arbitrary , overlapping features, input; part of: arbitrary , overlapping features, Markov model