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Dataset . 2022
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Dataset . 2022
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Webis Causal Question Answering 2022

Research datakeyboard_double_arrow_right Dataset 11 Oct 2022 English Publisher:Zenodo
Authors: Alexander Bondarenko; Magdalena Wolska; Stefan Heindorf; Lukas Blübaum; Axel-Cyrille Ngonga Ngomo; Benno Stein; Pavel Braslavski; +2 Authors

doi: 10.5281/zenodo.7186760 , 10.5281/zenodo.7186761 , 10.5281/zenodo.7476615

Webis Causal Question Answering 2022

Abstract

The Webis Causal Question Answering 2022 (Webis-CausalQA-22) corpus comprises 1.1M causal question-answer pairs collected from the public QA datasets. This dataset was developed to support the development of tailored approaches that can answer causal questions. Overview: The directory "input" contains the train and validation splits (used for evaluation), the directory "output" contains the evaluation results, and the directory "models" includes the fine-tuned checkpoints.

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Keywords

causal question answering, causal questions, question answering

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
OpenAIRE UsageCountsViews provided by UsageCounts
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