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Dataset Card for "sciq"
Dataset Summary
The SciQ dataset contains 13,679 crowdsourced science exam questions about Physics, Chemistry and Biology, among others. The questions are in multiple-choice format with 4 answer options each. For the majority of the questions, an additional paragraph with supporting evidence for the correct answer is provided.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
default
- Size of downloaded dataset files: 2.82 MB
- Size of the generated dataset: 7.68 MB
- Total amount of disk used: 10.50 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"correct_answer": "coriolis effect",
"distractor1": "muon effect",
"distractor2": "centrifugal effect",
"distractor3": "tropical effect",
"question": "What phenomenon makes global winds blow northeast to southwest or the reverse in the northern hemisphere and northwest to southeast or the reverse in the southern hemisphere?",
"support": "\"Without Coriolis Effect the global winds would blow north to south or south to north. But Coriolis makes them blow northeast to..."
}
Data Fields
The data fields are the same among all splits.
default
question: astringfeature.distractor3: astringfeature.distractor1: astringfeature.distractor2: astringfeature.correct_answer: astringfeature.support: astringfeature.
Data Splits
| name | train | validation | test |
|---|---|---|---|
| default | 11679 | 1000 | 1000 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
The dataset is licensed under the Creative Commons Attribution-NonCommercial 3.0 Unported License.
Citation Information
@inproceedings{SciQ,
title={Crowdsourcing Multiple Choice Science Questions},
author={Johannes Welbl, Nelson F. Liu, Matt Gardner},
year={2017},
journal={arXiv:1707.06209v1}
}
Contributions
Thanks to @patrickvonplaten, @lewtun, @thomwolf for adding this dataset.
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