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Automated extraction of semantic information from german legal documents

Last modified Jan 9

Abstract

Based on a collaborative data science environment, and a large document corpus (> 130.000 documents from German tax law) we demonstrate the extraction of semantic information. This paper shows the potential of rule-based text analysis to automatically extract semantic information, such as the year of dispute in cases. Additionally, it demonstrates the extraction of legal definitions in laws and the usage of terms in a defining context. Based on an iterative and interdisciplinary process, involving legal experts, software engineers, and data scientists, to evaluate and continuously refine the model used for the computer-supported extraction.

Files and Subpages

Name Type Size Last Modification Last Editor
Wa17a.pdf 218 KB 22.02.2017