Datasets:
metadata
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_sentence
dtype: string
splits:
- name: en
num_bytes: 24945
num_examples: 400
- name: ru
num_bytes: 48249
num_examples: 400
- name: uk
num_bytes: 40226
num_examples: 400
- name: de
num_bytes: 44940
num_examples: 400
- name: es
num_bytes: 30159
num_examples: 400
- name: am
num_bytes: 72606
num_examples: 400
- name: zh
num_bytes: 36219
num_examples: 400
- name: ar
num_bytes: 44668
num_examples: 400
- name: hi
num_bytes: 57291
num_examples: 400
download_size: 257508
dataset_size: 399303
configs:
- config_name: default
data_files:
- split: en
path: data/en-*
- split: ru
path: data/ru-*
- split: uk
path: data/uk-*
- split: de
path: data/de-*
- split: es
path: data/es-*
- split: am
path: data/am-*
- split: zh
path: data/zh-*
- split: ar
path: data/ar-*
- split: hi
path: data/hi-*
MultiParaDetox
This is the multilingual parallel dataset for text detoxification prepared for CLEF TextDetox 2024 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).
Now, only dev set toxic sentences are released. Dev set references and test set toxic sentences will be released later with the test phase of the competition!
The list of the sources for the original toxic sentences:
- English: Jigsaw, Unitary AI Toxicity Dataset
- Russian: Russian Language Toxic Comments, Toxic Russian Comments
- Ukrainian: Ukrainian Twitter texts
- Spanish: Detecting and Monitoring Hate Speech in Twitter, Detoxis, RoBERTuito: a pre-trained language model for social media text in Spanish
- German: GemEval 2018, 2021
- Amhairc: Amharic Hate Speech
- Arabic: OSACT4
- Hindi: Hostility Detection Dataset in Hindi, Overview of the HASOC track at FIRE 2019: Hate Speech and Offensive Content Identification in Indo-European Languages