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Here we search for the best automated classification approach for a set ofcomplex legal documents. Our classification task is not trivial: our aim is toclassify ca 30,000 public courthouse records from 12 states and 267 counties attwo different levels using nine sub-categories. Specifically, we investigatedwhether a fine-tuned large language model (LLM) can achieve the accuracy of abespoke custom-trained model, and what is the amount of fine-tuning necessary.

Classifying complex documents: comparing bespoke solutions to large language models