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Automated Attribute Extraction from Legal Proceedings (2310.12131v1)
Published 18 Oct 2023 in cs.IR
Abstract: The escalating number of pending cases is a growing concern world-wide. Recent advancements in digitization have opened up possibilities for leveraging 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.
- Subinay Adhikary (2 papers)
- Sagnik Das (9 papers)
- Sagnik Saha (13 papers)
- Procheta Sen (11 papers)
- Dwaipayan Roy (16 papers)
- Kripabandhu Ghosh (35 papers)