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Automated Attribute Extraction from Legal Proceedings

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arxiv 2310.12131 v1 pith:4OAIT2PS submitted 2023-10-18 cs.IR

classification cs.IR
keywords legalattributesdocumentsproceedingsprocessingrepresentationachievingadopting
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. Annotating Topical Legal Insights from Case Proceedings

    cs.AI 2026-07 conditional novelty 3.0 of 10

    LeDA is a legal annotation tool with dynamic tag creation and adjudication, used to tag 200 Indian Supreme Court cases with thematic concepts like 'Murder on parole.'

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