Utilizing Large Language Models for Information Extraction from Real Estate Transactions

arXiv:2404.18043v1 Announce Type: cross
Abstract: Real estate sales contracts contain crucial information for property transactions, but manual extraction of data can be time-consuming and error-prone. This paper explores the application of large language models, specifically transformer-based architectures, for automated information extraction from real estate contracts. We discuss challenges, techniques, and future directions in leveraging these models to improve efficiency and accuracy in real estate contract analysis.

abstract application architectures arxiv automated challenges cs.cl cs.lg data discuss error extraction information information extraction language language models large language large language models paper property real estate sales transactions transformer type