Atomic tasks from a complex task using NLP

I have a problem statement when I need to find all the tasks that the server had to do based on a complex task. Example, in a 3D modeling scenario, if the model is queried with a complex task such as rotate then the response should be something like:

  1. Select the object
  2. Rotate the object

Can we make this model learn on data that is manually prepared and then tune the model such that it can predict more complex tasks?

Topic sequence-to-sequence text-mining nlp

Category Data Science

About

Geeks Mental is a community that publishes articles and tutorials about Web, Android, Data Science, new techniques and Linux security.