---
language:
- en
- ru
- uk
- es
- de
- ar
- am
- hi
- zh
license: openrail++
dataset_info:
  features:
  - name: text
    dtype: string
  splits:
  - name: am
    num_bytes: 4573
    num_examples: 261
  - name: es
    num_bytes: 14683
    num_examples: 1195
  - name: ru
    num_bytes: 4169218
    num_examples: 140296
  - name: uk
    num_bytes: 153865
    num_examples: 7356
  - name: en
    num_bytes: 39323
    num_examples: 3386
  - name: zh
    num_bytes: 9031
    num_examples: 823
  - name: ar
    num_bytes: 6050
    num_examples: 430
  - name: hi
    num_bytes: 2771
    num_examples: 133
  - name: de
    num_bytes: 3497
    num_examples: 272
  download_size: 2040710
  dataset_size: 4403011
configs:
- config_name: default
  data_files:
  - split: am
    path: data/am-*
  - split: es
    path: data/es-*
  - split: ru
    path: data/ru-*
  - split: uk
    path: data/uk-*
  - split: en
    path: data/en-*
  - split: zh
    path: data/zh-*
  - split: ar
    path: data/ar-*
  - split: hi
    path: data/hi-*
  - split: de
    path: data/de-*
---

This is the compilation of 9 languages (English, Russian, Ukrainian, Spanish, German, Amharic, Arabic, Chinese, Hindi) toxic words lists which is used for [CLEF TextDetox 2024](https://pan.webis.de/clef24/pan24-web/text-detoxification.html) shared task.

The list of original sources:
* English: [link](https://github.com/coffee-and-fun/google-profanity-words/blob/main/data/en.txt)
* Russian: [link](https://github.com/s-nlp/rudetoxifier/blob/main/data/train/MAT_FINAL_with_unigram_inflections.txt)
* Ukrainian: [link](https://github.com/saganoren/obscene-ukr)
* Spanish: [link](https://github.com/facebookresearch/flores/blob/main/toxicity/README.md)
* German: [link](https://github.com/LDNOOBW/List-of-Dirty-Naughty-Obscene-and-Otherwise-Bad-Words)
* Amhairc: ours
* Arabic: ours
* Hindi: [link](https://github.com/facebookresearch/flores/blob/main/toxicity/README.md)

All credits go to the authors of the original toxic words lists.