Natural Language Processing in Legal Systems: Automating Document Analysis and Case Prediction
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Abstract
Natural Language Processing (NLP) is transforming the legal industry by automating document analysis and enhancing case prediction. This paper investigates the application of advanced NLP techniques, including transformer-based models, in processing legal texts, contracts, and case precedents. We present a pipeline for extracting key information, classifying legal documents, and predicting case outcomes based on historical data. Experimental results demonstrate significant time savings and accuracy improvements. Challenges such as data ambiguity, interpretability, and ethical considerations are discussed to guide the integration of NLP into legal systems.
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