Datasets:
Tasks:
Question Answering
Modalities:
Text
Formats:
parquet
Sub-tasks:
extractive-qa
Languages:
Russian
Size:
10K - 100K
ArXiv:
License:
| pretty_name: SberQuAD | |
| 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 | |
| dataset_info: | |
| 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 | |
| config_name: sberquad | |
| splits: | |
| - name: train | |
| num_bytes: 71631661 | |
| num_examples: 45328 | |
| - name: validation | |
| num_bytes: 7972977 | |
| num_examples: 5036 | |
| - name: test | |
| num_bytes: 36397848 | |
| num_examples: 23936 | |
| download_size: 66047276 | |
| dataset_size: 116002486 | |
| # 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 | |
| ``` | |
| @article{DBLP:journals/corr/abs-1912-09723, | |
| author = {Pavel Efimov and | |
| Leonid Boytsov and | |
| Pavel Braslavski}, | |
| title = {SberQuAD - Russian Reading Comprehension Dataset: Description and | |
| Analysis}, | |
| journal = {CoRR}, | |
| volume = {abs/1912.09723}, | |
| year = {2019}, | |
| url = {http://arxiv.org/abs/1912.09723}, | |
| eprinttype = {arXiv}, | |
| eprint = {1912.09723}, | |
| timestamp = {Fri, 03 Jan 2020 16:10:45 +0100}, | |
| biburl = {https://dblp.org/rec/journals/corr/abs-1912-09723.bib}, | |
| bibsource = {dblp computer science bibliography, https://dblp.org} | |
| } | |
| ``` | |
| ### Contributions | |
| Thanks to [@alenusch](https://github.com/Alenush) for adding this dataset. |