Datasets:
Tasks:
Question Answering
Sub-tasks:
extractive-qa
Languages:
Russian
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Annotations Creators:
crowdsourced
Source Datasets:
original
ArXiv:
Tags:
License:
File size: 4,956 Bytes
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---
annotations_creators:
- crowdsourced
language_creators:
- found
- crowdsourced
language:
- ru
license:
- unknown
multilinguality:
- monolingual
size_categories:
- 10K<n<100K
source_datasets:
- original
task_categories:
- question-answering
task_ids:
- extractive-qa
paperswithcode_id: sberquad
pretty_name: SberQuAD
dataset_info:
config_name: sberquad
features:
- name: id
dtype: int32
- name: title
dtype: string
- name: context
dtype: string
- name: question
dtype: string
- name: answers
sequence:
- name: text
dtype: string
- name: answer_start
dtype: int32
splits:
- name: train
num_bytes: 71631541
num_examples: 45328
- name: validation
num_bytes: 7972953
num_examples: 5036
- name: test
num_bytes: 36397776
num_examples: 23936
download_size: 10491714
dataset_size: 116002270
---
# Dataset Card for sberquad
## Table of Contents
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks](#supported-tasks-and-leaderboards)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Data Fields](#data-instances)
- [Data Splits](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Curation Rationale](#curation-rationale)
- [Source Data](#source-data)
- [Annotations](#annotations)
- [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
- [Social Impact of Dataset](#social-impact-of-dataset)
- [Discussion of Biases](#discussion-of-biases)
- [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
- [Contributions](#contributions)
## Dataset Description
- **Homepage:** [Needs More Information]
- **Repository:** https://github.com/sberbank-ai/data-science-journey-2017
- **Paper:** https://arxiv.org/abs/1912.09723
- **Leaderboard:** [Needs More Information]
- **Point of Contact:** [Needs More Information]
### 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](https://github.com/Alenush) for adding this dataset. |