A Dataset of German Legal Documents for Named Entity Recognition

• DOI: 10.48550/arxiv.2003.13016
• Publication Date: 2020-01-01
• Authors: Elena Leitner; Georg Rehm; Julián Moreno Sch...
• Keywords: Named Entity Recognition

We describe a dataset developed for Named Entity Recognition in German federal court decisions. It consists of approx. 67,000 sentences with over 2 million tokens. The resource contains 54,000 manually annotated entities, mapped to 19 fine-grained semantic classes: person, judge, lawyer, country, city, street, landscape, organization, company, institution, court, brand, law, ordinance, European legal norm, regulation, contract, decision, and literature. documents were, furthermore, automatically more than 35,000 TimeML-based time expressions. dataset, which is available under CC-BY 4.0 license the CoNNL-2002 format, was training an NER service EU project Lynx.