How to use Stanford Open IE with nltk

I am on an NLP project right now and I need to use Stanford Open information extraction tool with python (nltk if possible). I found a python wrapper

but it's poorly documented and does not give full functionality interface to Stanford Open IE. Any suggestion?

3 Answers
3

One approach is to use the CoreNLP Server, which outputs OpenIE triples (see, e.g., corenlp.run). Among other libraries, Stanford's Stanza library is written in Python can call a server instance to get annotations. Make sure to include all the required annotators: tokenize,ssplit,pos,lemma,ner,depparse,natlog,openie.

tokenize,ssplit,pos,lemma,ner,depparse,natlog,openie

I just found another way with pycorenlp and corenlp

nlp = StanfordCoreNLP(<<url_to_your_server>>)
text = "'the quick brown fox jumps over the lazy dog.'"
output = nlp.annotate(text, properties={
'annotators': 'tokenize, ssplit, pos, depparse, parse, openie',
'outputFormat': 'json'
})


and the properties can be found through the keys you can get from

print(output['sentences'][0].keys)


I am extending philipperemy's old wrapper. I have added support for jupyter and extended it to work with the current version of Stanford NLP.

You can access philipperemy's version from here
And my version from here. But please note that mine is still being developed. But, in case, you have feature requests, please feel free to reply to this post. I'll try to add them as time permits.

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