4 ms·

Thank you, I understand your use case better. If possible, could you talk a bit about your process for training your model? It looks like it is specific to leg

by akudha 3y ago

Thank you, I understand your use case better. If possible, could you talk a bit about your process for training your model? It looks like it is specific to legal documents, how easy/hard would it be to do the same for other types of documents? Also, what level of accuracy is good enough, for your use case?

mjr00 3y ago
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.)