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Data · dataset · 2022

HuggingFaceM4/SNLI-VE

Listed in Hugging Face Datasets

SNLI-VE is the dataset proposed for the Visual Entailment (VE) task investigated in Visual Entailment Task for Visually-Grounded Language Learning accpeted to NeurIPS 2018 ViGIL workshop).

Description

SNLI-VE is built on top of SNLI and Flickr30K. The problem that VE is trying to solve is to reason about the relationship between an image premise Pimage and a text hypothesis Htext.

Specifically, given an image as premise, and a natural language sentence as hypothesis, three labels (entailment, neutral and contradiction) are assigned based on the relationship conveyed by the (Pimage, Htext) entailment holds if there is enough evidence in Pimage to conclude that Htext is true. contradiction holds if there is enough evidence in Pimage to conclude that Htext is false. Otherwise, the relationship is neutral, implying the evidence in Pimage is insufficient to draw a conclusion about Htext.

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Where it is published

Catalogue records · 1

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Inferred from text
Image 75% · Text 75%
Provenance · 1 source records, 10 field assertions
SourceKeyLast seenRaw
Hugging Face DatasetsHuggingFaceM4/SNLI-VE14 d agoJSON v1
FieldAssertionExtractorEvidence
access_levelsource · Hugging Faceconnector:huggingface@1.0.0/gated
concepts[field].local:field:computer-science-aimapping · Hugging Faceconnector:huggingface@1.0.0
concepts[modality].local:modality:imageenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (75%)
concepts[modality].local:modality:textenrichment · Hugging Facekeyword-concept-rules@1.0.0title+description (75%)
created_datesource · Hugging Faceconnector:huggingface@1.0.0
descriptionsource · Hugging Faceconnector:huggingface@1.0.0/description
license_textsource · Hugging Faceconnector:huggingface@1.0.0
publication_datesource · Hugging Faceconnector:huggingface@1.0.0
titlesource · Hugging Faceconnector:huggingface@1.0.0/id
updated_datesource · Hugging Faceconnector:huggingface@1.0.0