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42 datasets found
  1. z

    args.me corpus

    • zenodo.org
    zip
    Updated Apr 1, 2020
  2. W

    args.me corpus

    • webis.de
    3274635, html
    Updated 2019
  3. h

    args_me

    • huggingface.co
    Updated Sep 9, 2023
  4. z

    Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20)

    • zenodo.org
    csv
    Updated May 1, 2020
  5. h

    paperswithcode

    • huggingface.co
    Updated Dec 30, 2021
  6. W

    Webis-ArgQuality-20

    • webis.de
    3780048
    Updated 2020
  7. i

    IBM Debater® - Recorded Debating Dataset - Release #2 (Compressed audio...

    • research.ibm.com
    Updated Sep 25, 2017
  8. i

    IBM Debater® - Recorded Debating Dataset - Release #2 (Full version) +...

    • research.ibm.com
    Updated Sep 25, 2017
  9. i

    IBM Debater® - Recorded Debating Dataset - Release #2 (Light version - no...

    • research.ibm.com
    Updated Sep 25, 2017
  10. i

    IBM Debater® - IBM-ArgQ-6.3kArgs - 6.3K arguments with point-wise quality...

    • research.ibm.com
    Updated Sep 25, 2017
  11. i

    IBM Debater® - IBM-ArgQ-Rank-30kArgs 30,497 arguments actively collected...

    • research.ibm.com
    Updated Sep 25, 2017
  12. i

    IBM Debater® - Sentiment Composition Lexicons Sentiment composition lexicons...

    • research.ibm.com
    Updated Sep 25, 2017
  13. i

    IBM Debater® - Wikipedia Category Stance 4603 Wikipedia categories and lists...

    • research.ibm.com
    Updated Sep 25, 2017
  14. i

    IBM Debater® - Debate Topic Expansion The Debate Topic Expansion dataset...

    • research.ibm.com
    Updated Sep 25, 2017
  15. i

    IBM Debater® - Thematic Clustering of Sentences Dataset A benchmark of...

    • research.ibm.com
    Updated Sep 25, 2017
  16. i

    IBM Debater® - Labeled Emphasized Words in Speech The dataset contains 2485...

    • research.ibm.com
    Updated Sep 25, 2017
  17. i

    IBM Debater® - Recorded Debating Dataset - Release #1 (Light version - no...

    • research.ibm.com
    Updated Sep 25, 2017
  18. i

    IBM Debater® - Recorded Debating Dataset - Release #5 (Light version - no...

    • research.ibm.com
    Updated Sep 25, 2017
  19. i

    IBM Debater® - Recorded Debating Dataset - Release #3 (Light version - no...

    • research.ibm.com
    Updated Sep 25, 2017
  20. i

    IBM Debater® - CoPA-Motion Labeling Matching of motions to CoPAs

    • research.ibm.com
    • cobweb.ninja
    Updated Sep 25, 2017
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Cite
Yamen Ajjour; Henning Wachsmuth; Johannes Kiesel; Martin Potthast; Matthias Hagen; Benno Stein (2020). args.me corpus [Dataset]. http://doi.org/10.5281/zenodo.3734893

args.me corpus

Explore at:
78 scholarly articles cite this dataset (View in Google Scholar)
zipAvailable download formats
Unique identifier
https://doi.org/10.5281/zenodo.3734893
Dataset updated
Apr 1, 2020
Dataset provided by
Paderborn University
Martin Luther University of Halle-Wittenberg
Bauhaus Universität Weimar
Leipzig University
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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