This is abso-f***ing-lutely blue-sky territory.
But it would be wonderous if a Gramplet was created which allowed a chunk of free-form text (handtyped, Notes of ‘Transcript’ type, or scraped from a webpage) to be sent to a set of Natural Language Processor and received back transformed content.
spaCy is a free, open-source library for advanced Natural Language Processing (NLP) in Python.
Even at the crudest levels, it probably already identifies key words and gives them grammatical context. – These are People (see Disable everything except NER (named entity recognition)). These are probably first names. These are dates. et cetera.
Just identifying blocks of Text that are significant and indicating context would help you target your efforts. (Like getting the teachers copy of Cliff’s Notes where they had highlighted material for good essay questions.
But this would be the “low-return on investment” test case. Once Gramps was talking to a NLP and had an example of how to accept processed data back, then the possibilities are unlimited.
This library HAS to be a huge resource suck. So it would be great if no resources were allocated until Text was feed into it and processing was manually triggered. And then after processing, it would be great to demonstrate de-allocating those resources.
Automatic processing and dynamic allocation might never be needed if early results showed that the library sucked wind as well as resources.