2020
DOI: 10.48550/arxiv.2012.10251
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A Benchmark Arabic Dataset for Commonsense Explanation

Saja AL-Tawalbeh,
Mohammad AL-Smadi

Abstract: Language comprehension and commonsense knowledge validation by machines are challenging tasks that are still under researched and evaluated for Arabic text. In this paper, we present a benchmark Arabic dataset for commonsense explanation. The dataset consists of Arabic sentences that does not make sense along with three choices to select among them the one that explains why the sentence is false. Furthermore, this paper presents baseline results to assist and encourage the future evaluation of research in this… Show more

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Cited by 1 publication
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“…169,000 tasks Arabic Benchmark [4] Explain why a text 12,000 problems Adapted does not make sense. Avicenna [1] Complete a 6000 records Crowd sourcing valid syllogism CA-EHN [84] Chinese word analogy 90,505 analogies Adapted Labelled by experts CIDER [49] Causal explanation 807 dialogues, Adapted datasets.…”
Section: Collections Of Elementary Mathematical Word Problemsmentioning
confidence: 99%
“…169,000 tasks Arabic Benchmark [4] Explain why a text 12,000 problems Adapted does not make sense. Avicenna [1] Complete a 6000 records Crowd sourcing valid syllogism CA-EHN [84] Chinese word analogy 90,505 analogies Adapted Labelled by experts CIDER [49] Causal explanation 807 dialogues, Adapted datasets.…”
Section: Collections Of Elementary Mathematical Word Problemsmentioning
confidence: 99%