Various online databases exist to make judgments accessible in the digital age. Before a legal practitioner can utilize state-of-the-art information retrieval features to retrieve relevant court rulings, the textual document must be processed. More importantly, many verdicts lack crucial semantic information which can be utilized within the search process. One piece of information that is frequently missed, as the judge is not adding it during the publication process within the court, is the so-called norm chain. This list contains the most relevant norms for the underlying decision.
Therefore this paper investigates the feasibility of automatically extracting the most relevant norms of a court ruling. A dataset constituting over 42k labeled court rulings was used in order to train different classifiers. While our models provide F1 performances of up to 0.77, they can undoubtedly be utilized within the editorial publication process to provide helpful suggestions.
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