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The Unreasonable Effectiveness Of Large Language Models In Zero-Shot Semantic Annotation Of Legal Texts, Jaromir Savelka, Kevin D. Ashley
The Unreasonable Effectiveness Of Large Language Models In Zero-Shot Semantic Annotation Of Legal Texts, Jaromir Savelka, Kevin D. Ashley
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The emergence of ChatGPT has sensitized the general public, including the legal profession, to large language models' (LLMs) potential uses (e.g., document drafting, question answering, and summarization). Although recent studies have shown how well the technology performs in diverse semantic annotation tasks focused on legal texts, an influx of newer, more capable (GPT-4) or cost-effective (GPT-3.5-turbo) models requires another analysis. This paper addresses recent developments in the ability of LLMs to semantically annotate legal texts in zero-shot learning settings. Given the transition to mature generative AI systems, we examine the performance of GPT-4 and GPT-3.5-turbo(-16k), comparing it to the previous …