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LREC-COLING 2024main

DARIUS: A Comprehensive Learner Corpus for Argument Mining in German-Language Essays

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/229hqikmqsvv

Abstract

In this paper, we present the DARIUS (Digital Argumentation Instruction for Science) corpus for argumentation quality on 4589 essays written by 1839 German secondary school students. The corpus is annotated according to a fine-grained annotation scheme, ranging from a broader perspective like content zones, to more granular features like argumentation coverage/reach and argumentative discourse units like claims and warrants. The features have inter-annotator agreements up to 0.83 Krippendorff’s α. The corpus and dataset are publicly available for further research in argument mining.

Details

Paper ID
lrec2024-main-0389
Pages
pp. 4356-4367
BibKey
schaller-etal-2024-darius
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • NS

    Nils-Jonathan Schaller

  • AH

    Andrea Horbach

  • LH

    Lars Ingver Höft

  • YD

    Yuning Ding

  • JB

    Jan Luca Bahr

  • JM

    Jennifer Meyer

  • TJ

    Thorben Jansen

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