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Table · dataset · 2022

12ml/e-CARE

Listed in Hugging Face Datasets

Dataset of (Du et al., 2022) (Unofficial reupload)

Description

Abstract

Understanding causality has vital importance for various Natural Language Processing (NLP) applications. Beyond the labeled instances, conceptual explanations of the causality can provide deep understanding of the causal fact to facilitate the causal reasoning process. However, such explanation information still remains absent in existing causal reasoning resources.

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In this paper, we fill this gap by presenting… See the full description on the dataset page: huggingface.co/datasets/12ml/e-CARE.

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Where it is published

Documentation and papers

Catalogue records · 1

Topics

Inferred from text
Machine learning 69%
Provenance · 1 source records, 11 field assertions
SourceKeyLast seenRaw
Hugging Face Datasets12ml/e-CARE14 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].anzsrc:group:4611enrichment · Hugging Facetaxonomy-embedding@1.1.0title+keywords+description (69%)
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].hf_modality:textsource · Hugging Faceconnector:huggingface@1.0.0
concepts[task].hf_task:multiple-choicesource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
concepts[task].hf_task:text-classificationsource · Hugging Faceconnector:huggingface@1.0.0/tags[task_categories:*]
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0