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MultiOpEd

Introduced by Siyi Liu et al. in MultiOpEd: A Corpus of Multi-Perspective News Editorials4 Jun 2021 archive 2025-07-28

MultiOpEd is a corpus of multi-perspective news editorials. It is an open-domain news editorial corpus that supports various tasks pertaining to the argumentation structure in news editorials, focusing on automatic perspective discovery. News editorial is a genre of persuasive text, where the argumentation structure is usually implicit. However, the arguments presented in an editorial typically center around a concise, focused thesis, which we refer to as their perspective. MultiOpEd aims at supporting the study of multiple tasks relevant to automatic perspective discovery, where a system is expected to produce a single-sentence thesis statement summarizing the arguments presented.

Benchmarks archive 2025-07-28

No leaderboard in the archive resolves to this dataset.

Papers archive 2025-07-28

No paper in the archive has a leaderboard row on this dataset; the archive counts 2 papers for it but never published that list.

Dataset loaders archive 2025-07-28

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Tasks archive 2025-07-28

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License archive 2025-07-28

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Modalities archive 2025-07-28

Languages archive 2025-07-28

Variants archive 2025-07-28

  • MultiOpEd

1 variant name, as the archive lists them.

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