Dataset Card for "esnli"
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://github.com/OanaMariaCamburu/e-SNLI
- Repository: More Information Needed
- Paper: More Information Needed
- Point of Contact: More Information Needed
- Size of downloaded dataset files: 195.04 MB
- Size of the generated dataset: 109.52 MB
- Total amount of disk used: 304.56 MB
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
Languages
Dataset Structure
We show detailed information for up to 5 configurations of the dataset.
Data Instances
plain_text
- Size of downloaded dataset files: 195.04 MB
- Size of the generated dataset: 109.52 MB
- Total amount of disk used: 304.56 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
: astring
feature.hypothesis
: astring
feature.label
: a classification label, with possible values includingentailment
(0),neutral
(1),contradiction
(2).explanation_1
: astring
feature.explanation_2
: astring
feature.explanation_3
: astring
feature.
Data Splits Sample Size
name | train | validation | test |
---|---|---|---|
plain_text | 549367 | 9842 | 9824 |
Dataset Creation
Curation Rationale
Source Data
Annotations
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
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.