metadata

dataset_info:
  features:
    - name: Utterance
      dtype: string
    - name: politeness
      dtype: float64
    - name: language
      dtype: string
    - name: __index_level_0__
      dtype: int64
  splits:
    - name: train
      num_bytes: 4954742
      num_examples: 18238
    - name: validation
      num_bytes: 619659
      num_examples: 2280
    - name: test
      num_bytes: 619627
      num_examples: 2280
  download_size: 3919716
  dataset_size: 6194028
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: validation
        path: data/validation-*
      - split: test
        path: data/test-*

Dataset Card for "multilingual_politeness"

This dataset has the following attributes:

Utterance: a 2-3 sentence excerpt from Wikipedia editor talk pages.
language: English, Spanish, Chinese, or Japanese
politeness: An annotated politeness label ranging from -2 (very rude) to 2 (very polite). Each utterance was annotated by 3 native speakers.

Please cite the following paper if you use our dataset :)

@inproceedings{havaldar-etal-2023-comparing,
    title = "Comparing Styles across Languages",
    author = "Havaldar, Shreya  and Pressimone, Matthew  and Wong, Eric  and Ungar, Lyle",
    booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
    year = "2023",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2023.emnlp-main.419"
}