That's true, but assumes you have the checklist of what data to analyze in hand when you start out. If you only decide after the fact which familial relationships have interesting trends, you'd have to start over again. It seems more reasonable to start by transcribing everything to text, annotating that text, and then running a lot of scripting to automatically query that data.

Ok, obviously it's _doable_, but is it worth it? Using LLMs for this purpose would have been significantly cheaper, easier and with the right configuration just as reliable. Once the setup works, you could extend the analysis to all kinds of other interesting branches without having to look at a single speech by hand.

I would even go so far as to say that _not_ using LLMs for this task would be fairly odd, unless I'm missing something or the author really enjoys a month of manually classifying documents to write an interesting and well-written but not exceedingly outstanding article.