The automated summarisation of long legal documents can be a great aid for legal experts in their daily work. We automatically create summaries (guiding principles) of German judgments by fine-tuning a decoder-based large language model. We enrich the judgments with information about legal entities before the training. For the evaluation of the created summaries, we define a set of evaluation classes which allows us to measure their language, pertinence, completeness and correctness. Our results show that employing legal entities helps the generative model to find the relevant content, but the quality of the created summaries is not yet sufficient for a use in practice.
View on arXiv@article{steffes2025_2505.05947,
title={ Summarisation of German Judgments in conjunction with a Class-based Evaluation },
author={ Bianca Steffes and Nils Torben Wiedemann and Alexander Gratz and Pamela Hochreither and Jana Elina Meyer and Katharina Luise Schilke },
journal={arXiv preprint arXiv:2505.05947},
year={ 2025 }
}