---
language:
- en
- uk
- ru
- de
- zh
- am
- ar
- hi
- es
license: openrail++
size_categories:
- 1K<n<10K
task_categories:
- text-generation
dataset_info:
  features:
  - name: toxic_comment
    dtype: string
  splits:
  - name: es
    num_bytes: 30159
    num_examples: 400
  download_size: 23546
  dataset_size: 30159
configs:
- config_name: default
  data_files:
  - split: es
    path: data/es-*
---
**MultiParaDetox**

This is the multilingual parallel dataset for text detoxification prepared for [CLEF TextDetox 2024](https://pan.webis.de/clef24/pan24-web/text-detoxification.html) shared task.
For each of 9 languages, we collected 1k pairs of toxic<->detoxified instances splitted into two parts: dev (400 pairs) and test (600 pairs). 

**Dev set references and test set toxic sentences will be released later!**

The list of the sources for the original toxic sentences:
* English: [Jigsaw](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge), [Unitary AI Toxicity Dataset](https://github.com/unitaryai/detoxify)
* Russian: [Russian Language Toxic Comments](https://www.kaggle.com/datasets/blackmoon/russian-language-toxic-comments), [Toxic Russian Comments](https://www.kaggle.com/datasets/alexandersemiletov/toxic-russian-comments)
* Ukrainian: [Ukrainian Twitter texts](https://github.com/saganoren/ukr-twi-corpus)
* Spanish: TBD
* German: [GemEval 2018, 2021](https://aclanthology.org/2021.germeval-1.1/)
* Amhairc: [Amharic Hate Speech](https://github.com/uhh-lt/AmharicHateSpeech)
* Arabic: [OSACT4](https://edinburghnlp.inf.ed.ac.uk/workshops/OSACT4/)
* Hindi: [Hostility Detection Dataset in Hindi](https://competitions.codalab.org/competitions/26654#learn_the_details-dataset), [Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages](https://dl.acm.org/doi/pdf/10.1145/3368567.3368584?download=true)