Automating operations and maintenance manual data extraction for retrofit applications: assessing GPT-4o’s performance and challenges
Haoyu Zuo, Yuan Yin, Kaymar Hazeri, Boheng Wang et autres
Operations & Maintenance (O&M) manuals contain data that is essential to understand ahead of building retrofits. However, their unstructured format makes information retrieval time-consuming and error-prone. This study evaluates GPT-4o’s ability to extract information from O&M manuals, assessing accuracy in text extraction, …
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Spiral (Imperial College London)