GGPONC: A Corpus of German Medical Text with Rich Metadata Based on Clinical Practice Guidelines
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Abstract (arXiv)
The lack of publicly accessible text corpora is a major obstacle for progress in natural language processing. For medical applications, unfortunately, all language communities other than English are low-resourced. In this work, we present GGPONC (German Guideline Program in Oncology NLP Corpus), a freely distributable German language corpus based on clinical practice guidelines for oncology. This corpus is one of the largest ever built from German medical documents. Unlike clinical documents, clinical guidelines do not contain any patient-related information and can therefore be used without data protection restrictions. Moreover, GGPONC is the first corpus for the German language covering diverse conditions in a large medical subfield and provides a variety of metadata, such as literature references and evidence levels. By applying and evaluating existing medical information extraction pipelines for German text, we are able to draw comparisons for the use of medical language to other corpora, medical and non-medical ones.
Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). First posted on arXiv 13 Jul 2020.
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Citing papers per year: 2021: 1; 2022: 2; 2023: 2; 2024: 1; 2025: 0; 2026: 1.
7 papers.
- 2023MEDBERT.de: A Comprehensive German BERT Model for the Medical Domaincited by 10
- 2022GERNERMED++: Transfer Learning in German Medical NLPcited by 3
- 2022A Medical Information Extraction Workbench to Process German Clinical Textcited by 2
- 2021GERNERMED -- An Open German Medical NER Modelcited by 0
- 2023FastDoc: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomycited by 0
- 2024Comprehensive Study on German Language Models for Clinical and Biomedical Text Understandingcited by 0
- 2026From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelinescited by 0
- 2026From PDF to Evidence: Structure-Aware Retrieval for Clinical Practice Guidelines27 Sep 2026
- 2024Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding8 Apr 2024
- 2023FastDoc: Domain-Specific Fast Continual Pre-training Technique using Document-Level Metadata and Taxonomy9 Jun 2023
- 2023MEDBERT.de: A Comprehensive German BERT Model for the Medical Domain14 Mar 2023
- 2022A Medical Information Extraction Workbench to Process German Clinical Text8 Jul 2022
- 2022GERNERMED++: Transfer Learning in German Medical NLP29 Jun 2022
- 2021GERNERMED -- An Open German Medical NER Model24 Sep 2021