- Description:
A new dataset of 7,787 genuine grade-school level, multiple-choice science questions, assembled to encourage research in advanced question-answering. The dataset is partitioned into a Challenge Set and an Easy Set, where the former contains only questions answered incorrectly by both a retrieval-based algorithm and a word co-occurrence algorithm. We are also including a corpus of over 14 million science sentences relevant to the task, and an implementation of three neural baseline models for this dataset. We pose ARC as a challenge to the community.
Compared to the original dataset, this adds context sentences obtained through information retrieval in the same way as UnifiedQA (see: https://arxiv.org/abs/2005.00700 ).
Additional Documentation: Explore on Papers With Code
Homepage: https://allenai.org/data/arc
Source code:
tfds.datasets.ai2_arc_with_ir.Builder
Versions:
1.0.0
(default): No release notes.
Download size:
3.68 MiB
Auto-cached (documentation): Yes
Feature structure:
FeaturesDict({
'answerKey': ClassLabel(shape=(), dtype=int64, num_classes=5),
'choices': Sequence({
'label': ClassLabel(shape=(), dtype=int64, num_classes=5),
'text': Text(shape=(), dtype=string),
}),
'id': Text(shape=(), dtype=string),
'paragraph': Text(shape=(), dtype=string),
'question': Text(shape=(), dtype=string),
})
- Feature documentation:
Feature | Class | Shape | Dtype | Description |
---|---|---|---|---|
FeaturesDict | ||||
answerKey | ClassLabel | int64 | ||
choices | Sequence | |||
choices/label | ClassLabel | int64 | ||
choices/text | Text | string | ||
id | Text | string | ||
paragraph | Text | string | ||
question | Text | string |
Supervised keys (See
as_supervised
doc):None
Figure (tfds.show_examples): Not supported.
Citation:
@article{allenai:arc,
author = {Peter Clark and Isaac Cowhey and Oren Etzioni and Tushar Khot and
Ashish Sabharwal and Carissa Schoenick and Oyvind Tafjord},
title = {Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge},
journal = {arXiv:1803.05457v1},
year = {2018},
}
@article{2020unifiedqa,
title={UnifiedQA: Crossing Format Boundaries With a Single QA System},
author={D. Khashabi and S. Min and T. Khot and A. Sabhwaral and O. Tafjord and P. Clark and H. Hajishirzi},
journal={arXiv preprint},
year={2020}
}
ai2_arc_with_ir/ARC-Challenge-IR (default config)
Config description: Challenge Set of 2590 "hard" questions (those that both a retrieval and a co-occurrence method fail to answer correctly)
Dataset size:
3.76 MiB
Splits:
Split | Examples |
---|---|
'test' |
1,172 |
'train' |
1,119 |
'validation' |
299 |
- Examples (tfds.as_dataframe):
ai2_arc_with_ir/ARC-Easy-IR
Config description: Easy Set of 5197 questions for the ARC Challenge.
Dataset size:
7.49 MiB
Splits:
Split | Examples |
---|---|
'test' |
2,376 |
'train' |
2,251 |
'validation' |
570 |
- Examples (tfds.as_dataframe):