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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Jhofenbitzer/GerMedIQ-Corpus: Official Github Repository of the GerMedIQ Corpus

Authors: Hofenbitzer, Justin; Schöning, Sebastian; Belle, Sebastian; Lammert, Jacqueline; Modersohn, Luise; Boeker, Martin; Frassinelli, Diego;

Jhofenbitzer/GerMedIQ-Corpus: Official Github Repository of the GerMedIQ Corpus

Abstract

German Medical Interview Questions (GerMedIQ) Corpus This repository contains the GerMedIQ corpus, a dataset of 4,524 unique simulated question-response pairs from the medical domain in German. Specifically, the corpus consists of 116 anamnesis questions from standardized medical interview questionnaires answered by 39 non-patient participants. The questions are extracted from 12 baseline anamnesis questionnaires as well as from the EORTC Quality of Life Questionnaire, the PainDETECT Questionnaire, and the Barthel Index. Along with the simulated responses, an LLM-augmented addition of the corpus can be found, too. The responses from the LLMs were created by 18 small, medium-sized, and large biomedical or general-domain LLMs in a zero-shot approach. For further details, refer to our paper. This Repo Analysis: Contains R Markdown files used for statistical evaluations and plotting. CorpusFiles: Contains the GerMedIQ corpus CSV files. EvaluationResults: Contains some evaluation results. Judgments: Contains the judgments obtained from the LLM-judges and the human raters. Scripts: Contains all scripts used. Citations This repository accompanies the publication GerMedIQ: A Resource for Simulated and Synthesized Anamnesis Interview Responses in German (ACL SRW 2025). Please cite both the publication and the Zenodo record when using this resource: @InProceedings{hofenbitzer2025germediq, author = {Hofenbitzer, Justin and Sch{\"o}ning, Sebastian and Belle, Sebastian and Lammert, Jacqueline and Modersohn, Luise and Boeker, Martin and Frassinelli, Diego}, booktitle = {Proceedings of the 63rd {Annual} {Meeting} of the {Association} for {Computational} {Linguistics} ({Volume} 4: {Student} {Research} {Workshop})}, title = {{GerMedIQ}: {A} {Resource} for {Simulated} and {Synthesized} {Anamnesis} {Interview} {Responses} in {German}}, year = {2025}, address = {Vienna, Austria}, editor = {Zhao, Jin and Wang, Mingyang and Liu, Zhu}, month = jul, pages = {1064--1078}, publisher = {Association for Computational Linguistics}, doi = {10.18653/v1/2025.acl-srw.84}, isbn = {9798891762541}, url = {https://aclanthology.org/2025.acl-srw.84/},}, @Misc{hofenbitzer2025jhofenbitzer, author = {Justin Hofenbitzer and Sch{\"o}ning, Sebastian and Belle, Sebastian and Lammert, Jacqueline and Modersohn, Luise and Boeker, Martin and Frassinelli, Diego}, title = {{Jhofenbitzer/GerMedIQ-Corpus: Official Github Repository of the GerMedIQ Corpus}}, year = {2025}, copyright = {Creative Commons Attribution 4.0 International}, doi = {10.5281/zenodo.1646062}, publisher = {Zenodo}, } Poster View and Download the poster: https://zenodo.org/records/17047376 License This dataset is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) license. You are free to: Share – copy and redistribute the material in any medium or format Adapt – remix, transform, and build upon the material for any purpose, even commercially Under the following terms: Attribution – You must give appropriate credit, provide a link to the license, and indicate if changes were made. For full details, see: https://creativecommons.org/licenses/by/4.0/.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average