q_re_cc

• Description:

A dataset containing 14K conversations with 81K question-answer pairs. QReCC is built on questions from TREC CAsT, QuAC and Google Natural Questions.

• Homepage: https://github.com/apple/ml-qrecc

• Source code: tfds.text.qrecc.QReCC

• Versions:

  • 1.0.0 (default): Initial release.

• Download size: 7.60 MiB

• Dataset size: 69.29 MiB

• Auto-cached (documentation): Yes

• Splits:

Split	Examples
'test'	16,451
'train'	63,501

• Feature structure:

FeaturesDict({
    'answer': Text(shape=(), dtype=string),
    'answer_url': Text(shape=(), dtype=string),
    'context': Sequence(Text(shape=(), dtype=string)),
    'conversation_id': Scalar(shape=(), dtype=int32, description=The id of the conversation.),
    'question': Text(shape=(), dtype=string),
    'question_rewrite': Text(shape=(), dtype=string),
    'source': Text(shape=(), dtype=string),
    'turn_id': Scalar(shape=(), dtype=int32, description=The id of the conversation turn, within a conversation.),
})

• Feature documentation:

Feature	Class	Shape	Dtype	Description
	FeaturesDict
answer	Text		string
answer_url	Text		string
context	Sequence(Text)	(None,)	string
conversation_id	Scalar		int32	The id of the conversation.
question	Text		string
question_rewrite	Text		string
source	Text		string	The original source of the data -- either QuAC, CAsT or Natural Questions
turn_id	Scalar		int32	The id of the conversation turn, within a conversation.

• Supervised keys (See as_supervised doc): None

• Figure (tfds.show_examples): Not supported.

• Examples (tfds.as_dataframe):

• Citation:

@article{qrecc,
  title={Open-Domain Question Answering Goes Conversational via Question Rewriting},
  author={Anantha, Raviteja and Vakulenko, Svitlana and Tu, Zhucheng and Longpre, Shayne and Pulman, Stephen and Chappidi, Srinivas},
  journal={Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies},
  year={2021}
}