LLMs reach 80% weighted F1 on German employment contract clause review when given lawyer-distilled examination guidelines, but lag human lawyers when reading full legal sources.
Team UTSA-NLP at SemEval 2024 Task 5: Prompt Ensembling for Argument Reasoning in Civil Procedures with GPT4
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abstract
In this paper, we present our system for the SemEval Task 5, The Legal Argument Reasoning Task in Civil Procedure Challenge. Legal argument reasoning is an essential skill that all law students must master. Moreover, it is important to develop natural language processing solutions that can reason about a question given terse domain-specific contextual information. Our system explores a prompt-based solution using GPT4 to reason over legal arguments. We also evaluate an ensemble of prompting strategies, including chain-of-thought reasoning and in-context learning. Overall, our system results in a Macro F1 of .8095 on the validation dataset and .7315 (5th out of 21 teams) on the final test set. Code for this project is available at https://github.com/danschumac1/CivilPromptReasoningGPT4.
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LLMs for Legal Subsumption in German Employment Contracts
LLMs reach 80% weighted F1 on German employment contract clause review when given lawyer-distilled examination guidelines, but lag human lawyers when reading full legal sources.