esnli

• Description:

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

• Additional Documentation: Explore on Papers With Code

• Homepage: https://github.com/OanaMariaCamburu/e-SNLI

• Source code: tfds.text.Esnli

• Versions:

  • 0.1.0 (default): No release notes.

• Download size: 195.04 MiB

• Dataset size: 161.94 MiB

• Auto-cached (documentation): Yes (test, validation), Only when shuffle_files=False (train)

• Splits:

Split	Examples
'test'	9,824
'train'	549,367
'validation'	9,842

• Feature structure:

FeaturesDict({
    'explanation_1': Text(shape=(), dtype=string),
    'explanation_2': Text(shape=(), dtype=string),
    'explanation_3': Text(shape=(), dtype=string),
    'hypothesis': Text(shape=(), dtype=string),
    'label': ClassLabel(shape=(), dtype=int64, num_classes=3),
    'premise': Text(shape=(), dtype=string),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
explanation_1	Text		string
explanation_2	Text		string
explanation_3	Text		string
hypothesis	Text		string
label	ClassLabel		int64
premise	Text		string

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@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}
}