esnli

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Cannot get the config names for the dataset.

Error code:   ConfigNamesError
Exception:    RuntimeError
Message:      Dataset scripts are no longer supported, but found esnli.py
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 67, in compute_config_names_response
                  config_names = get_dataset_config_names(
                      path=dataset,
                      token=hf_token,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/inspect.py", line 161, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                      path,
                  ...<4 lines>...
                      **download_kwargs,
                  )
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1182, in dataset_module_factory
                  raise e1 from None
                File "/usr/local/lib/python3.14/site-packages/datasets/load.py", line 1142, in dataset_module_factory
                  raise RuntimeError(f"Dataset scripts are no longer supported, but found {filename}")
              RuntimeError: Dataset scripts are no longer supported, but found esnli.py

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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

More Information Needed

Languages

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Dataset Structure

Data Instances

plain_text

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.

plain_text

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

name	train	validation	test
plain_text	549367	9842	9824

Dataset Creation

Curation Rationale

More Information Needed

Source Data

Initial Data Collection and Normalization

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Who are the source language producers?

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Annotations

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}
}