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NLP to extract actions from text

I hope someone can point me in the right direction to learn how to separate actions from a bunch of text.

Suppose I have this text

  Drop off the dry cleaning, and go to the corner store and pick-up a jug of milk and get a pint of strawberries.
 Then, go pick up the kids from school.  First, get John who is in the daycare next to the library, and then get Sam who is two blocks away. 
 By the time you've got the kids, you'll need to stop by the doctors office for the perscription.  Tim flight arrives at 4pm. 
 It American Airlines flight 331 arriving from Dallas.  It will be getting close to rush hour, so make sure you leave yourself enough time.

I'm trying to break it into

  Drop off the dry cleaning,

  and go to the corner store and pick-up a jug of milk and get a pint of strawberries.

  Then, go pick up the kids from school.  First, get John who is in the daycare next to the library, and then get Sam who is two blocks away. 

  By the time you've got the kids, you'll need to stop by the doctors office for the perscription. 
  Tim flight arrives at 4pm. 
 It American Airlines flight 331 arriving from Dallas.  It will be getting close to rush hour, so make sure you leave yourself enough time.

I was unable to find anything in my search queries that was specifically based on action. This should be smarter than just picking verbs, as there are several verbs that are sometimes associated with one action, for example, the second element has “go,” “pickup,” and “receive,” but it's all part of one action. Of course, Tim’s flight offers only action with real participle, the verb is approaching the end of the segment.

Any suggestions on where to look for such things? Things to watch, recommended readings, etc. Etc.

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2 answers

A simple approach: analyze the text using [your favorite parser], then select sentences or SBAR phrases that are in an imperative mood. The Stanford parser just so happened that in its latest issue of "Improved recognition of imperatives."

There is probably no need for machine learning besides what is already included in standard parser programs.

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This domain is called Information Retrieval .

General approach to understanding the proposals:

  • extract partial expression parsing pairs (Python spaCy.io, nltk, CoreNLP, etc.).
  • extracting a vector word (e.g. word2vec)
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Source: https://habr.com/ru/post/1381914/

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