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Dataset Card for sberquad
Dataset Summary
Sber Question Answering Dataset (SberQuAD) is a reading comprehension dataset, consisting of questions posed by crowdworkers on a set of Wikipedia articles, where the answer to every question is a segment of text, or span, from the corresponding reading passage, or the question might be unanswerable. Russian original analogue presented in Sberbank Data Science Journey 2017.
Supported Tasks and Leaderboards
[Needs More Information]
Languages
Russian
Dataset Structure
Data Instances
{
"context": "Первые упоминания о строении человеческого тела встречаются в Древнем Египте...",
"id": 14754,
"qas": [
{
"id": 60544,
"question": "Где встречаются первые упоминания о строении человеческого тела?",
"answers": [{"answer_start": 60, "text": "в Древнем Египте"}],
}
]
}
Data Fields
- id: a int32 feature
- title: a string feature
- context: a string feature
- question: a string feature
- answers: a dictionary feature containing:
- text: a string feature
- answer_start: a int32 feature
Data Splits
name | train | validation | test |
---|---|---|---|
plain_text | 45328 | 5036 | 23936 |
Dataset Creation
Curation Rationale
[Needs More Information]
Source Data
Initial Data Collection and Normalization
[Needs More Information]
Who are the source language producers?
[Needs More Information]
Annotations
Annotation process
[Needs More Information]
Who are the annotators?
[Needs More Information]
Personal and Sensitive Information
[Needs More Information]
Considerations for Using the Data
Social Impact of Dataset
[Needs More Information]
Discussion of Biases
[Needs More Information]
Other Known Limitations
[Needs More Information]
Additional Information
Dataset Curators
[Needs More Information]
Licensing Information
[Needs More Information]
Citation Information
@InProceedings{sberquad,
doi = {10.1007/978-3-030-58219-7_1},
author = {Pavel Efimov and
Andrey Chertok and
Leonid Boytsov and
Pavel Braslavski},
title = {SberQuAD -- Russian Reading Comprehension Dataset: Description and Analysis},
booktitle = {Experimental IR Meets Multilinguality, Multimodality, and Interaction},
year = {2020},
publisher = {Springer International Publishing},
pages = {3--15}
}
Contributions
Thanks to @alenusch for adding this dataset.
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