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
- name: neutral_sentence
dtype: string
splits:
- name: en
num_bytes: 47435
num_examples: 400
- name: ru
num_bytes: 89453
num_examples: 400
- name: uk
num_bytes: 78106
num_examples: 400
- name: de
num_bytes: 86818
num_examples: 400
- name: es
num_bytes: 56868
num_examples: 400
- name: am
num_bytes: 133489
num_examples: 400
- name: zh
num_bytes: 79089
num_examples: 400
- name: ar
num_bytes: 85237
num_examples: 400
- name: hi
num_bytes: 107518
num_examples: 400
download_size: 489288
dataset_size: 764013
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).
!!!April, 23rd, update: We are realsing the parallel dev set! The test part for the final phase of the competition is available here!!!
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