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Automated Attribute Extraction from Legal Proceedings

2023-10-18 · Subinay Adhikary, Sagnik Das, Sagnik Saha, Procheta Sen, Dwaipayan Roy, Kripabandhu Ghosh

The escalating number of pending cases is a growing concern world-wide. Recent advancements in digitization have opened up possibilities for leveraging artificial intelligence (AI) tools in the processing of legal documents. Adopting a structured representation for legal documents, as opposed to a mere bag-of-words flat text representation, can significantly enhance processing capabilities. With the aim of achieving this objective, we put forward a set of diverse attributes for criminal case proceedings. We use a state-of-the-art sequence labeling framework to automatically extract attributes from the legal documents. Moreover, we demonstrate the efficacy of the extracted attributes in a downstream task, namely legal judgment prediction.

📄 PDF Abstract BibTeX arXiv:2310.12131

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Tasks

AttributeAttribute Extraction

Methods 이 논문이 사용한 방법론

SET Dynamic Sparse Training method where weight mask is updated randomly periodically

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