google/flan-t5-large
Text2Text Generation
•
Updated
•
1.36M
•
•
614
Dataset Viewer
Full Screen Viewer
Full Screen
The viewer is disabled because this dataset repo requires arbitrary Python code execution. Please consider
removing the
loading script
and relying on
automated data support
(you can use
convert_to_parquet
from the datasets library). If this is not possible, please
open a discussion
for direct help.
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
Languages
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: astringfeature.hypothesis: astringfeature.label: a classification label, with possible values includingentailment(0),neutral(1),contradiction(2).explanation_1: astringfeature.explanation_2: astringfeature.explanation_3: astringfeature.
Data Splits
| name | train | validation | test |
|---|---|---|---|
| plain_text | 549367 | 9842 | 9824 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
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.
- Downloads last month
- 218