Datasets:
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README.md
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license: openrail++
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size_categories:
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- 1K<n<10K
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- split: hi
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path: data/hi-*
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---
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- am
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- ar
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- hi
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- es
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license: openrail++
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size_categories:
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- 1K<n<10K
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- split: hi
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path: data/hi-*
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---
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**MultiParaDetox**
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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.
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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!**
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The list of the sources for the original toxic sentences:
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* English: [Jigsaw](https://www.kaggle.com/c/jigsaw-toxic-comment-classification-challenge), [Unitary AI Toxicity Dataset](https://github.com/unitaryai/detoxify)
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* 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)
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* Ukrainian: [Ukrainian Twitter texts](https://github.com/saganoren/ukr-twi-corpus)
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* Spanish: TBD
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* German: [GemEval 2018, 2021](https://aclanthology.org/2021.germeval-1.1/)
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* Amhairc: [Amharic Hate Speech](https://github.com/uhh-lt/AmharicHateSpeech)
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* Arabic: [OSACT4](https://edinburghnlp.inf.ed.ac.uk/workshops/OSACT4/)
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* 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)
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