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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 .
 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
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:
 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