Datasets:
metadata
dataset_info:
features:
- name: question
dtype: string
- name: answer
dtype: string
- name: turker_answer
dtype: string
- name: rule-based
dtype: string
- name: dataset
dtype: string
- name: example_uid
dtype: string
splits:
- name: train
num_bytes: 17334203
num_examples: 60710
- name: validation
num_bytes: 2964727
num_examples: 10344
download_size: 15067362
dataset_size: 20298930
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
- split: validation
path: data/validation-*
license: mit
task_categories:
- text2text-generation
language:
- sk
pretty_name: QA2D-sk
size_categories:
- 10K<n<100K
Slovak version of the Question to Declarative Sentence (QA2D). Machine-translated using DeepL service.
For more information, see our Pipeline and Dataset Generation for Automated Fact-checking in Almost Any Language paper. Currently in review for NCAA journal.
@article{drchal2023pipeline,
title={Pipeline and Dataset Generation for Automated Fact-checking in Almost Any Language},
author={Drchal, Jan and Ullrich, Herbert and Mlyn{\'a}{\v{r}}, Tom{\'a}{\v{s}} and Moravec, V{\'a}clav},
journal={arXiv preprint arXiv:2312.10171},
year={2023}
}