![](bg7.png)
unseen German legal documents and analyse their
contents.
The judgement corpus can be used for writ-
ing style detection in free text. Furthermore, it
is possible to look into the inner workings of the
judgement. Which conclusion is connected to
which definition and which definition belongs
to which subsumption. Additionally, judgements
from different courts could be compared in order to
answer whether there are big differences between the
writing styles of the courts.
Based on the work presented in Mitrovi
´
c et
al. (Mitrovi
´
c et al., 2017) writing style components
can be represented ontologically, and their persua-
siveness assessed based on the rhetorical elements
contained therein.
6 CONCLUSION
This paper presents two novel German legal corpora
based on Bavarian Court decisions between 2015 and
2020.
The first one contains 32,748 decisions from 131
German courts. A model that predicts the type of de-
cision was trained on this corpus. Resulting in a pre-
cision of 0.97.
The second corpus is a subset of the first one.
200 judgements were randomly chosen and annotated
with conclusion, definition, subsumption and
other, components of the Urteilsstil. On this cor-
pus several models were trained to predict to which
component a sentence of a judgement belongs. The
baseline is always outperformed, however no clear
best approach could be determined. LR performs well
with unigrams and SCV performs the same with tf-
idf.
Both corpora are published on the open science
platform zenodo.
In future work different legal experts will inspect
the existing labels to ensure the label quality.
ACKNOWLEDGEMENTS
The annotation of the judgement corpus was only pos-
sible due to the help and funding from the research
centre FREDI
13
.
The project on which this report is based was
funded by the German Federal Ministry of Educa-
tion and Research (BMBF) under the funding code
01—S20049. The author is responsible for the con-
tent of this publication.
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forschungseinrichtungen/forschungsstelle-fredi/
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