StanfordCoreNLP openIE issue

Question

I am facing the same issue as Stanford CoreNLP OpenIE annotator I try output = nlp.annotate(s, properties={"annotators":"tokenize,ssplit,pos,depparse,natlog,openie", "outputFormat": "json","openie.triple.strict":"true", "openie.max_entailments_per_clause":"1","openie.splitter.disable":"true"})

But still I get 4 clauses

(u'are pulled from', u'Twenty percent electric motors', u'assembly line') (u'are pulled from', u'percent electric motors', u'assembly line') (u'are', u'Twenty percent electric motors', u'pulled') (u'are', u'percent electric motors', u'pulled') Am I doing anything wrong? How to get precise triple ('are pulled from', 'Twenty percent electric motors', 'assembly line')

Answer 1

This is actually expected behavior. It was a design decision in the OpenIE system to produce all triples which are logically entailed by the original sentence, even if they are redundant. The idea being that these triples are usually used for something akin to IR-ish lookup, and in these cases it's convenient to not have to do fuzzy matching for whether any of the triples are "similar enough" to the query.