openbookqa

Description:

The dataset contains 5,957 4-way multiple choice questions. Additionally, they provide 5,167 crowd-sourced common knowledge facts, and an expanded version of the train/dev/test questions where each question is associated with its originating core fact, a human accuracy score, a clarity score, and an anonymized crowd-worker ID.

Homepage: https://leaderboard.allenai.org/open_book_qa/submissions/get-started
Source code: tfds.text.Openbookqa
Versions:
- 0.1.0 (default): No release notes.
Download size: 1.38 MiB
Dataset size: 2.40 MiB
Auto-cached (documentation): Yes
Splits:

Split	Examples
`'test'`	500
`'train'`	4,957
`'validation'`	500

Feature structure:

FeaturesDict({
    'answerKey': ClassLabel(shape=(), dtype=tf.int64, num_classes=4),
    'clarity': tf.float32,
    'fact1': Text(shape=(), dtype=tf.string),
    'humanScore': tf.float32,
    'question': FeaturesDict({
        'choice_A': Text(shape=(), dtype=tf.string),
        'choice_B': Text(shape=(), dtype=tf.string),
        'choice_C': Text(shape=(), dtype=tf.string),
        'choice_D': Text(shape=(), dtype=tf.string),
        'stem': Text(shape=(), dtype=tf.string),
    }),
    'turkIdAnonymized': Text(shape=(), dtype=tf.string),
})

Feature documentation:

Feature	Class	Dtype
	FeaturesDict
answerKey	ClassLabel	tf.int64
clarity	Tensor	tf.float32
fact1	Text	tf.string
humanScore	Tensor	tf.float32
question	FeaturesDict
question/choice_A	Text	tf.string
question/choice_B	Text	tf.string
question/choice_C	Text	tf.string
question/choice_D	Text	tf.string
question/stem	Text	tf.string
turkIdAnonymized	Text	tf.string

Supervised keys (See as_supervised doc): ('question', 'answerKey')
Figure (tfds.show_examples): Not supported.
Examples (tfds.as_dataframe):

Citation:

@article{mihaylov2018can,
  title={Can a suit of armor conduct electricity? a new dataset for open book question answering},
  author={Mihaylov, Todor and Clark, Peter and Khot, Tushar and Sabharwal, Ashish},
  journal={arXiv preprint arXiv:1809.02789},
  year={2018}
}