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Data are presented which show how a connectionist -LRB- neural -RRB- network trained with linguistic rules can parse both expected -LRB- grammatical -RRB- sentences as well as some novel -LRB- ungrammatical or lexically ambiguous -RRB- sentences .
 used for: connectionist -LRB- neural -RRB- network, expected -LRB- grammatical -RRB- sentences; used for: connectionist -LRB- neural -RRB- network, -LRB- ungrammatical or lexically ambiguous -RRB- sentences; used for: linguistic rules, connectionist -LRB- neural -RRB- network; conjunction: expected -LRB- grammatical -RRB- sentences, -LRB- ungrammatical or lexically ambiguous -RRB- sentences
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:  connectionist -LRB- neural -RRB- network, expected -LRB- grammatical -RRB- sentences; connectionist -LRB- neural -RRB- network, -LRB- ungrammatical or lexically ambiguous -RRB- sentences; linguistic rules, connectionist -LRB- neural -RRB- network; expected -LRB- grammatical -RRB- sentences, -LRB- ungrammatical or lexically ambiguous -RRB- sentences 
Answer:
 used for: connectionist -LRB- neural -RRB- network, expected -LRB- grammatical -RRB- sentences; used for: connectionist -LRB- neural -RRB- network, -LRB- ungrammatical or lexically ambiguous -RRB- sentences; used for: linguistic rules, connectionist -LRB- neural -RRB- network; conjunction: expected -LRB- grammatical -RRB- sentences, -LRB- ungrammatical or lexically ambiguous -RRB- sentences