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An Automated Framework for the Extraction of Semantic Legal Metadata from Legal Texts
Our work is motivated by two observations: (1) the existing requirements engineering (RE) literature does not provide a harmonized view on the semantic metadata types that are useful for legal requirements analysis; (2) automated support for the extraction of semantic legal metadata is scarce, and it does not exploit the full potential of artificial intelligence technologies, notably natural language processing (NLP) and machine learning (ML).
Software Engineering
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