1 dataset found
- W
Webis-CausalQA-22
- webis.de
- anthology.aicmu.ac.cn
7186761Updated 2022
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EmailClick to copy linkLink copiedCiteAlexander Bondarenko; Magdalena Wolska; Stefan Heindorf; Pavel Braslavski; Benno Stein; Matthias Hagen; Martin Potthast (2022). Webis-CausalQA-22 [Dataset]. http://doi.org/10.5281/zenodo.71867617186761Available download formatsUnique identifierhttps://doi.org/10.5281/zenodo.7186761Dataset updated2022Dataset provided byCombinatorial Algebra Lab, Ural Federal University
Leipzig University and Friedrich Schiller University Jena
University of Kassel, hessian.AI, and ScaDS.AI
Universität Paderborn
Bauhaus-Universität Weimar
Friedrich Schiller University Jena
The Web Technology & Information Systems NetworkAuthorsAlexander Bondarenko; Magdalena Wolska; Stefan Heindorf; Pavel Braslavski; Benno Stein; Matthias Hagen; Martin PotthastLicenseAttribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automaticallyDescriptionThe Webis Causal Question Answering 2022 (Webis-CausalQA-22) corpus comprises 1.1M causal question-answer pairs collected from the public QA datasets.
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Alexander Bondarenko; Magdalena Wolska; Stefan Heindorf; Pavel Braslavski; Benno Stein; Matthias Hagen; Martin Potthast (2022). Webis-CausalQA-22 [Dataset]. http://doi.org/10.5281/zenodo.7186761
7186761Available download formats
Unique identifier
https://doi.org/10.5281/zenodo.7186761Dataset updated
2022Dataset provided by
Combinatorial Algebra Lab, Ural Federal University Leipzig University and Friedrich Schiller University Jena
University of Kassel, hessian.AI, and ScaDS.AI
Universität Paderborn
Bauhaus-Universität Weimar
Friedrich Schiller University Jena
The Web Technology & Information Systems Network
Authors
Alexander Bondarenko; Magdalena Wolska; Stefan Heindorf; Pavel Braslavski; Benno Stein; Matthias Hagen; Martin Potthast License
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Description
The Webis Causal Question Answering 2022 (Webis-CausalQA-22) corpus comprises 1.1M causal question-answer pairs collected from the public QA datasets.