DECODEM: Data Extraction from Corporate Organizational Documents via Enhanced Methods

arXiv:2607.15879v3 Announce Type: replace-cross Abstract: Much empirical legal research depends on translating unstructured text into structured variables. In corporate governance research as elsewhere, this translation has traditionally been performed by humans. Manual coding is time-consuming and costly. In corporate governance research, standardized commercial datasets offer an alternative, but they cover a limited set of firms and governance variables. This paper introduces the DECODEM Benchmarks and uses them to evaluate whether large language models can extract corporate governance varia

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