3 ms·

I was only considering doing it manually. I don't know how feasible it would be to automate the conversion process. The formatting and language used in these "e

• sova 10y ago
  Honestly, this seems like one of the more realistic problems NLP could actually solve. Yes there may be many variants, say 100 or even 1000 different structures and vocabularies for updating versions, but a differential neural network where you have inputs (like the pre-amended law) and outputs (like the laws after the "amendments" or version bumps) would actually be perfect for learning what means what and when to do it. It would be the perfect grad project for someone interesting in bridging the gap between computation/machine learning and legislation. Of course, it would be a little tedious setting up the learning (thousands of sets of input cases and output cases) but in the end the findings could be used across the board.