Published October 27, 2020 | Version 1.0-cleaned
Dataset Open

args.me corpus

  • 1. Bauhaus Universität Weimar
  • 2. Paderborn University
  • 3. Leipzig University
  • 4. Martin Luther University of Halle-Wittenberg

Description

The args.me corpus (version 1.0, cleaned) comprises 382 545 arguments crawled from four debate portals in the middle of 2019. The debate portals are Debatewise, IDebate.org, Debatepedia, and Debate.org. The arguments are extracted using heuristics that are designed for each debate portal.

This version contains the same arguments as Version 1.0, but cleaned as described in the corresponding publication.

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.

Cite the cleaning procedure as TODO.

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.

Files

argsme-1.0-cleaned.zip

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Additional details

References

  • 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.
  • 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.