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This is for a personal project, and I am no very skilled programmer, language is Python, needs to work offline. That said: I have a list of 200 key actions, eg. 'Building sandcastles', 'Paintball' or 'Swinging at the playground'. And I have about a page of natural text loosely revolving around some of these actions. How do I detect where the natural text mentions one of these actions, and which one?

Ideally this would be something smart, some easy-to-use machine learning Python NLP library, which I can just feed my keywords and natural text. But it would need to be something straightforward, as I'm not skilled enough to set this up myself. What libraries should I be looking at?

As a non-smart fallback, I could imagine processing my keywords (eg. removing stop words and Swinging > swing, so verb declination does not interfere) and search for these strings in my natural text. But how would I do that in a sensible way?

If this should be the wrong forum, please let me know where to go instead. And needless to say, any help is appreciated a lot, thanks in advance!

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