- 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}
}