The beauty of it is there's no model training involved: it's quite literally a prompt that reads something like "given the following document, output JSON that

The beauty of it is there's no model training involved: it's quite literally a prompt that reads something like "given the following document, output JSON that contains the following information: a field name `"widget"` that contains widget name, etc..." then including the doc right into the prompt. This was written a while ago so it just iterates in a python script dividing the source document up and aggregating to get around context length limits. Extremely simple, but works great. I don't have a really specific accuracy target but since my main interest is in the aggregated results it's not a huge deal if the aggregations are slightly off. (The manual human approach is not 100% accurate either, after all; it's extremely common for humans to make data entry mistakes.)