Automated Attribute Extraction from Legal Proceedings
Automated Attribute Extraction from Legal Proceedings
Subinay Adhikary, Sagnik Das, Sagnik Saha, Procheta Sen, Dwaipayan Roy, Kripabandhu Ghosh
AbstractThe 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.