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This project is broken into 2 sub projects:
- NLP – Sentencias: The project aims to use NLP to extract procedural history from “sentencias” to build predictive models for case timelines, ultimately demonstrating the value of structured data to the judiciary and potentially influencing standardization practices, while also providing insights for public policy interventions and serving as a proof of concept for data science applications in court systems globally.
- NLP – Law Text Summarization: The current goal is to summarize legal documents from the clearinghouse.net to automate work they’ve been doing with law students