README.md

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: 17257995
      num_examples: 60710
    - name: validation
      num_bytes: 2947806
      num_examples: 10344
  download_size: 14891492
  dataset_size: 20205801
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
license: mit
task_categories:
  - text2text-generation
language:
  - cs
pretty_name: QA2D-cs
size_categories:
  - 10K<n<100K

Czech 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}
}