Dataset Card for "esnli"

Dataset Summary

The e-SNLI dataset extends the Stanford Natural Language Inference Dataset to include human-annotated natural language explanations of the entailment relations.

Supported Tasks and Leaderboards

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Languages

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Dataset Structure

Data Instances

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• Size of downloaded dataset files: 204.51 MB
• Size of the generated dataset: 114.84 MB
• Total amount of disk used: 319.35 MB

An example of 'validation' looks as follows.

{
    "explanation_1": "A woman must be present to smile.",
    "explanation_2": "A woman smiling implies that she is present.",
    "explanation_3": "A smiling woman is also present.",
    "hypothesis": "A woman is present.",
    "label": 0,
    "premise": "A woman smiles at the child."
}

Data Fields

The data fields are the same among all splits.

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• premise: a string feature.
• hypothesis: a string feature.
• label: a classification label, with possible values including entailment (0), neutral (1), contradiction (2).
• explanation_1: a string feature.
• explanation_2: a string feature.
• explanation_3: a string feature.

Data Splits

Dataset Creation

Curation Rationale

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Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

Annotation process

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Who are the annotators?

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Personal and Sensitive Information

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Considerations for Using the Data

Social Impact of Dataset

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Discussion of Biases

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Other Known Limitations

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Additional Information

Dataset Curators

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Licensing Information

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Citation Information

@incollection{NIPS2018_8163,
title = {e-SNLI: Natural Language Inference with Natural Language Explanations},
author = {Camburu, Oana-Maria and Rockt"{a}schel, Tim and Lukasiewicz, Thomas and Blunsom, Phil},
booktitle = {Advances in Neural Information Processing Systems 31},
editor = {S. Bengio and H. Wallach and H. Larochelle and K. Grauman and N. Cesa-Bianchi and R. Garnett},
pages = {9539--9549},
year = {2018},
publisher = {Curran Associates, Inc.},
url = {http://papers.nips.cc/paper/8163-e-snli-natural-language-inference-with-natural-language-explanations.pdf}
}

Contributions

Thanks to @thomwolf, @lewtun, @albertvillanova, @patrickvonplaten for adding this dataset.