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Populating legal ontologies using semantic role labeling
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DOI：10.1007/s10506-020-09271-3.png)
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Abstract
En 中文
This article seeks to address the problem of the 'resource consumption bottleneck' of creating legal semantic technologies manually. It describes a semantic role labeling based information extraction system to extract definitions and norms from legislation and represent them as structured norms in legal ontologies. The output is intended to help make laws more accessible, understandable, and searchable in a legal document management system.
Keywords:
Classification
Information extraction
Ontology
Normative reasoning
Semantic role labeling
Artificial intelligence
Law
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