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This paper proposes a Hidden Markov Model -LRB- HMM -RRB- and an HMM-based chunk tagger , from which a named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system is built to recognize and classify names , times and numerical quantities .
 conjunction: Hidden Markov Model -LRB- HMM -RRB-, HMM-based chunk tagger; used for: Hidden Markov Model -LRB- HMM -RRB-, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; used for: HMM-based chunk tagger, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; used for: named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, names; used for: named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, times and numerical quantities; conjunction: names, times and numerical quantities
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:  Hidden Markov Model -LRB- HMM -RRB-, HMM-based chunk tagger; Hidden Markov Model -LRB- HMM -RRB-, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; HMM-based chunk tagger, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, names; named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, times and numerical quantities; names, times and numerical quantities 
Answer:
 conjunction: Hidden Markov Model -LRB- HMM -RRB-, HMM-based chunk tagger; used for: Hidden Markov Model -LRB- HMM -RRB-, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; used for: HMM-based chunk tagger, named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system; used for: named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, names; used for: named entity -LRB- NE -RRB- recognition -LRB- NER -RRB- system, times and numerical quantities; conjunction: names, times and numerical quantities