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I'm pretty sure someone has faced this basic issue in the past. You send a wall of text to the MS Cognitive Services Linguistic Analysis engine and it returns you a pile of tokens back with the text you sent in. (A tokenized version of your text). Then, all you want is a Noun and a Verb from each sentence.

Basically,

  For Each Paragraph in MyWallOfText
    For Each Sentence in Paragraph
      MyNoun = ResultOfMagicCode(Sentence, "Noun")
      MyVerb = ResultOfMagicCode(Sentence, "Verb")
    }
  }

But I find examples not.

Has anyone seen such a library, an example, has an example, has a library, has suggestions, has appropriate memes, has clues?

Thanks.

user1582732
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  • I believe your question is already answered:[Parser for Constituency Tree (Linguistics Analysis API)](https://stackoverflow.com/questions/41518425/parser-for-constituency-tree-linguistics-analysis-api/41520440#41520440http://) – BSalita May 31 '17 at 09:36
  • BSalita: Actually, no it doesn't. That particular code example is a full blown all the bells and whistles Honda Gold Wing of an example when I'm looking for a basic Mini Bike version. (bell okay) It's exceptionally complex and includes a yuge level of concepts that totally detract from the intended goal. Bad! However, I found something more to my liking with the 'MS Azure Machine Learning - Text Analytics' thingy. It's really what I wanted. Find the important phrases in a wall of text and then rate them by frequency. I still don't know how to work with Json but I are on the right path. – user1582732 Jun 01 '17 at 23:10

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