--- configs: - config_name: default data_files: - split: uk path: data/uk-* - split: hi path: data/hi-* - split: zh path: data/zh-* - split: ar path: data/ar-* - split: de path: data/de-* - split: en path: data/en-* - split: ru path: data/ru-* - split: am path: data/am-* - split: es path: data/es-* - split: it path: data/it-* - split: fr path: data/fr-* - split: he path: data/he-* - split: hin path: data/hin-* - split: tt path: data/tt-* - split: ja path: data/ja-* dataset_info: features: - name: text dtype: string splits: - name: uk num_bytes: 64010 num_examples: 600 - name: hi num_bytes: 84742 num_examples: 600 - name: zh num_bytes: 51159 num_examples: 600 - name: ar num_bytes: 67319 num_examples: 600 - name: de num_bytes: 68242 num_examples: 600 - name: en num_bytes: 37872 num_examples: 600 - name: ru num_bytes: 73326 num_examples: 600 - name: am num_bytes: 110756 num_examples: 600 - name: es num_bytes: 40172 num_examples: 600 - name: it num_bytes: 60915 num_examples: 600 - name: fr num_bytes: 56925 num_examples: 600 - name: he num_bytes: 73387 num_examples: 600 - name: hin num_bytes: 43652 num_examples: 600 - name: tt num_bytes: 69603 num_examples: 600 - name: ja num_bytes: 68980 num_examples: 600 download_size: 620757 dataset_size: 971060 --- **Multilingual Text Detoxification with Parallel Data (Test)** **[May, 2025]** The full [TextDetox2025](https://pan.webis.de/clef25/pan25-web/text-detoxification.html) test set is now available! **[2025]** For the second edition of [TextDetox2025 shared](https://pan.webis.de/clef25/pan25-web/text-detoxification.html) task, we extend to more languages: Italian, French, Hebrew, Hinglish, Japanese, and Tatar! **[2024]** 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). ### !! This is a **test** part of Multilingual Paradetox. For the **train** part please refer to [textdetox/multilingual_paradetox](https://huggingface.co/datasets/textdetox/multilingual_paradetox) 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: [Detecting and Monitoring Hate Speech in Twitter](https://www.mdpi.com/1424-8220/19/21/4654), [Detoxis](https://rdcu.be/dwhxH), [RoBERTuito: a pre-trained language model for social media text in Spanish](https://aclanthology.org/2022.lrec-1.785/) * 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) * Italian: [AMI](https://github.com/dnozza/ami2020), [HODI](https://github.com/HODI-EVALITA/HODI_2023), [Jigsaw Multilingual Toxic Comment](https://www.kaggle.com/competitions/jigsaw-multilingual-toxic-comment-classification/overview) * French: [FrenchToxicityPrompts](https://europe.naverlabs.com/research/publications/frenchtoxicityprompts-a-large-benchmark-for-evaluating-and-mitigating-toxicity-in-french-texts/), [Jigsaw Multilingual Toxic Comment](https://www.kaggle.com/competitions/jigsaw-multilingual-toxic-comment-classification/overview) * Hebrew: [Hebrew Offensive Language Dataset](https://github.com/NataliaVanetik/HebrewOffensiveLanguageDatasetForTheDetoxificationProject/tree/main) * Hinglish: [Hinglish Hate Detection](https://github.com/victor7246/Hinglish_Hate_Detection/blob/main/data/raw/trac1-dataset/hindi/agr_hi_dev.csv) * Japanese: posts from [2chan](https://huggingface.co/datasets/p1atdev/open2ch) * Tatar: ours. ## Citation If you would like to acknowledge our work, please, cite the following manuscripts: ``` @inproceedings{dementieva2024overview, title={Overview of the Multilingual Text Detoxification Task at PAN 2024}, author={Dementieva, Daryna and Moskovskiy, Daniil and Babakov, Nikolay and Ayele, Abinew Ali and Rizwan, Naquee and Schneider, Frolian and Wang, Xintog and Yimam, Seid Muhie and Ustalov, Dmitry and Stakovskii, Elisei and Smirnova, Alisa and Elnagar, Ashraf and Mukherjee, Animesh and Panchenko, Alexander}, booktitle={Working Notes of CLEF 2024 - Conference and Labs of the Evaluation Forum}, editor={Guglielmo Faggioli and Nicola Ferro and Petra Galu{\v{s}}{\v{c}}{\'a}kov{\'a} and Alba Garc{\'i}a Seco de Herrera}, year={2024}, organization={CEUR-WS.org} } ``` ``` @inproceedings{DBLP:conf/ecir/BevendorffCCDEFFKMMPPRRSSSTUWZ24, author = {Janek Bevendorff and Xavier Bonet Casals and Berta Chulvi and Daryna Dementieva and Ashaf Elnagar and Dayne Freitag and Maik Fr{\"{o}}be and Damir Korencic and Maximilian Mayerl and Animesh Mukherjee and Alexander Panchenko and Martin Potthast and Francisco Rangel and Paolo Rosso and Alisa Smirnova and Efstathios Stamatatos and Benno Stein and Mariona Taul{\'{e}} and Dmitry Ustalov and Matti Wiegmann and Eva Zangerle}, editor = {Nazli Goharian and Nicola Tonellotto and Yulan He and Aldo Lipani and Graham McDonald and Craig Macdonald and Iadh Ounis}, title = {Overview of {PAN} 2024: Multi-author Writing Style Analysis, Multilingual Text Detoxification, Oppositional Thinking Analysis, and Generative {AI} Authorship Verification - Extended Abstract}, booktitle = {Advances in Information Retrieval - 46th European Conference on Information Retrieval, {ECIR} 2024, Glasgow, UK, March 24-28, 2024, Proceedings, Part {VI}}, series = {Lecture Notes in Computer Science}, volume = {14613}, pages = {3--10}, publisher = {Springer}, year = {2024}, url = {https://doi.org/10.1007/978-3-031-56072-9\_1}, doi = {10.1007/978-3-031-56072-9\_1}, timestamp = {Fri, 29 Mar 2024 23:01:36 +0100}, biburl = {https://dblp.org/rec/conf/ecir/BevendorffCCDEFFKMMPPRRSSSTUWZ24.bib}, bibsource = {dblp computer science bibliography, https://dblp.org} } ```