esnli

  • Description:

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

Split Examples
'test' 9,824
'train' 549,367
'validation' 9,842
  • Feature structure:
FeaturesDict({
    'explanation_1': Text(shape=(), dtype=tf.string),
    'explanation_2': Text(shape=(), dtype=tf.string),
    'explanation_3': Text(shape=(), dtype=tf.string),
    'hypothesis': Text(shape=(), dtype=tf.string),
    'label': ClassLabel(shape=(), dtype=tf.int64, num_classes=3),
    'premise': Text(shape=(), dtype=tf.string),
})
  • Feature documentation:
Feature Class Shape Dtype Description
FeaturesDict
explanation_1 Text tf.string
explanation_2 Text tf.string
explanation_3 Text tf.string
hypothesis Text tf.string
label ClassLabel tf.int64
premise Text tf.string
  • 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}
}