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4 datasets found
  1. args.me corpus

    • zenodo.org
    zip
    Updated Apr 1, 2020
  2. args.me corpus

    • webis.de
    json
    Updated 2019
  3. args.me corpus

    • search.datacite.org
    Updated Oct 27, 2020
  4. webis-argquality-20

    • webis.de
    • zenodo.org
    csv
    Updated 2020
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Yamen Ajjour; Henning Wachsmuth; Johannes Kiesel; Martin Potthast; Matthias Hagen; Benno Stein (2020). args.me corpus [Dataset]. http://doi.org/10.5281/zenodo.3734893
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args.me corpus

59 scholarly articles cite this dataset (View in Google Scholar)
zipAvailable download formats
Dataset updated
Apr 1, 2020
Dataset provided by
Leipzig Universityhttp://www.uni-leipzig.de/
Paderborn Universityhttp://www.uni-paderborn.de/
Martin-Luther-University Halle-Wittenberghttp://www.uchicago.edu/
Bauhaus-Universität Weimarhttp://www.uni-weimar.de/
Authors
Yamen Ajjour; Henning Wachsmuth; Johannes Kiesel; Martin Potthast; Matthias Hagen; Benno Stein
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Description

The args.me corpus comprises 387 740 arguments. They are crawled from the debate portals Debatewise (14 353 arguments), IDebate.org (13 522 arguments), Debatepedia (21 197 arguments), and Debate.org (338 620 arguments). Moreover, the corpus contains 48 arguments from Canadian Parliament discussions. The arguments are extracted using heuristics that are designed for each debate portal.

These arguments are the ones currently provided through the args.me search engine. Note that the args API does not return the sourceText (which is indexed by args.me an included in this dataset) due to its size.

Cite args.me as Henning Wachsmuth, Martin Potthast, Khalid Al-Khatib, Yamen Ajjour, Jana Puschmann, Jiani Qu, Jonas Dorsch, Viorel Morari, Janek Bevendorff, and Benno Stein. Building an Argument Search Engine for the Web. In 4th Workshop on Argument Mining (ArgMining 2017) at EMNLP, pages 49-59, September 2017. Association for Computational Linguistics.

Cite this dataset as Yamen Ajjour, Henning Wachsmuth, Johannes Kiesel, Martin Potthast, Matthias Hagen, and Benno Stein. Data Acquisition for Argument Search: The args.me corpus. In 42nd German Conference on Artificial Intelligence (KI 2019), September 2019. Springer. and with the DOI of Zenodo.

The development for args.me is hosted in our Gitlab.

This collection is licensed with the Creative Commons Attribution 4.0 International. Individual rights to the content still apply.

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