Datasets:
Tasks:
Question Answering
Languages:
English
Multilinguality:
monolingual
Size Categories:
1K<n<10K
Language Creators:
found
Annotations Creators:
expert-generated
Source Datasets:
original
Tags:
License:
annotations_creators: | |
- expert-generated | |
language_creators: | |
- found | |
language: | |
- en | |
license: | |
- apache-2.0 | |
multilinguality: | |
- monolingual | |
size_categories: | |
- 1K<n<10K | |
source_datasets: | |
- original | |
task_categories: | |
- question-answering | |
task_ids: | |
- closed-domain-qa | |
- extractive-qa | |
paperswithcode_id: null | |
pretty_name: COVID-QA | |
dataset_info: | |
features: | |
- name: document_id | |
dtype: int32 | |
- name: context | |
dtype: string | |
- name: question | |
dtype: string | |
- name: is_impossible | |
dtype: bool | |
- name: id | |
dtype: int32 | |
- name: answers | |
sequence: | |
- name: text | |
dtype: string | |
- name: answer_start | |
dtype: int32 | |
config_name: covid_qa_deepset | |
splits: | |
- name: train | |
num_bytes: 65151262 | |
num_examples: 2019 | |
download_size: 4418117 | |
dataset_size: 65151262 | |
# Dataset Card for COVID-QA | |
## Table of Contents | |
- [Dataset Description](#dataset-description) | |
- [Dataset Summary](#dataset-summary) | |
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) | |
- [Languages](#languages) | |
- [Dataset Structure](#dataset-structure) | |
- [Data Instances](#data-instances) | |
- [Data Fields](#data-fields) | |
- [Data Splits](#data-splits) | |
- [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 | |
- **Repository:** https://github.com/deepset-ai/COVID-QA | |
- **Paper:** https://openreview.net/forum?id=JENSKEEzsoU | |
- **Point of Contact:** [deepset AI](https://github.com/deepset-ai) | |
### Dataset Summary | |
COVID-QA is a Question Answering dataset consisting of 2,019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19. | |
A total of 147 scientific articles from the CORD-19 dataset were annotated by 15 experts. | |
### Supported Tasks and Leaderboards | |
[More Information Needed] | |
### Languages | |
The text in the dataset is in English. | |
## Dataset Structure | |
### Data Instances | |
**What do the instances that comprise the dataset represent?** | |
Each represents a question, a context (document passage from the CORD19 dataset) and an answer. | |
**How many instances are there in total?** | |
2019 instances | |
**What data does each instance consist of?** | |
Each instance is a question, a set of answers, and an id associated with each answer. | |
[More Information Needed] | |
### Data Fields | |
The data was annotated in SQuAD style fashion, where each row contains: | |
* **question**: Query question | |
* **context**: Context text to obtain the answer from | |
* **document_id** The document ID of the context text | |
* **answer**: Dictionary containing the answer string and the start index | |
### Data Splits | |
**data/COVID-QA.json**: 2,019 question/answer pairs annotated by volunteer biomedical experts on scientific articles related to COVID-19. | |
[More Information Needed] | |
## Dataset Creation | |
### Curation Rationale | |
[More Information Needed] | |
### Source Data | |
#### Initial Data Collection and Normalization | |
The inital data collected comes from 147 scientific articles from the CORD-19 dataset. Question and answers were then | |
annotated afterwards. | |
#### Who are the source language producers? | |
[More Information Needed] | |
### Annotations | |
#### Annotation process | |
While annotators were volunteers, they were required to have at least a Master’s degree in biomedical sciences. | |
The annotation team was led by a medical doctor (G.A.R.) who vetted the volunteer’s credentials and | |
manually verified each question/answer pair produced. We used an existing, web-based annotation tool that had been | |
created by deepset and is available at their Neural Search framework [haystack](https://github.com/deepset-ai/haystack). | |
#### Who are the annotators? | |
The annotators are 15 volunteer biomedical experts on scientific articles related to COVID-19. | |
### Personal and Sensitive Information | |
[More Information Needed] | |
## Considerations for Using the Data | |
### Social Impact of Dataset | |
The dataset aims to help build question answering models serving clinical and scientific researchers, public health authorities, and frontline workers. | |
These QA systems can help them find answers and patterns in research papers by locating relevant answers to common questions from scientific articles. | |
### Discussion of Biases | |
[More Information Needed] | |
### Other Known Limitations | |
## Additional Information | |
The listed authors in the homepage are maintaining/supporting the dataset. | |
### Dataset Curators | |
[More Information Needed] | |
### Licensing Information | |
The Proto_qa dataset is licensed under the [Apache License 2.0](https://github.com/deepset-ai/COVID-QA/blob/master/LICENSE) | |
### Citation Information | |
``` | |
@inproceedings{moller2020covid, | |
title={COVID-QA: A Question Answering Dataset for COVID-19}, | |
author={M{\"o}ller, Timo and Reina, Anthony and Jayakumar, Raghavan and Pietsch, Malte}, | |
booktitle={Proceedings of the 1st Workshop on NLP for COVID-19 at ACL 2020}, | |
year={2020} | |
} | |
``` | |
### Contributions | |
Thanks to [@olinguyen](https://github.com/olinguyen) for adding this dataset. |