This repository contains parallel detoxification dataset for the task of elimination toxicity from the texts. The pipeline used for this dataset collection was presented in "Crowdsourcing of Parallel Corpora: the Case of Style Transfer for Detoxification" paper presented at VLDB 2021 Crowd Science Workshop.
The whole pipeline of the collection was divided into three tasks:
- Task 1: detoxified paraphrase generation;
- Task 2: content preservation check of obtained results from Task 1;
- Task 3: toxicity check of obtained results from Task 1;
Here you can see the schematical illustration of the collection pipeline:
Currenlty, the dataset consists of 2,779 pairs of toxic sentence <-> detoxified sentence. The unique toxic sentences covered are 1108. For each toxic sentence there no more than 4 detoxified sentence.
Example of samples:
| toxic_comment | civil_comment |
|---|---|
| this is scaring the shit out of me. | This is really scaring me. |
| this is a joke , are you all fucking retards? | This is a joke, are you all crazy? |
| all you trump clowns are seriously messed up. | Trumps voters are seriously mislead. |
If you find this repository helpful, feel free to cite our publication:
@inproceedings{dementieva2021crowdsourcing,
title = "Crowdsourcing of Parallel Corpora: the Case of Style Transfer for Detoxification",
author = {Dementieva, Daryna
and Ustyantsev, Sergey
and Dale, David
and Kozlova, Olga
and Semenov, Nikita
and Panchenko, Alexander
and Logacheva, Varvara},
booktitle = "Proceedings of the 2nd Crowd Science Workshop: Trust, Ethics, and Excellence in Crowdsourced Data Management at Scale co-located with 47th International Conference on Very Large Data Bases (VLDB 2021 (https://vldb.org/2021/))",
year = "2021",
address = "Copenhagen, Denmark",
publisher = "CEUR Workshop Proceedings",
pages = "35--49",
url={http://ceur-ws.org/Vol-2932/paper2.pdf}
}
and check the latest version of the English ParaDetox in:
@inproceedings{logacheva-etal-2022-paradetox,
title = "{P}ara{D}etox: Detoxification with Parallel Data",
author = "Logacheva, Varvara and
Dementieva, Daryna and
Ustyantsev, Sergey and
Moskovskiy, Daniil and
Dale, David and
Krotova, Irina and
Semenov, Nikita and
Panchenko, Alexander",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.469",
pages = "6804--6818",
abstract = "We present a novel pipeline for the collection of parallel data for the detoxification task. We collect non-toxic paraphrases for over 10,000 English toxic sentences. We also show that this pipeline can be used to distill a large existing corpus of paraphrases to get toxic-neutral sentence pairs. We release two parallel corpora which can be used for the training of detoxification models. To the best of our knowledge, these are the first parallel datasets for this task.We describe our pipeline in detail to make it fast to set up for a new language or domain, thus contributing to faster and easier development of new parallel resources.We train several detoxification models on the collected data and compare them with several baselines and state-of-the-art unsupervised approaches. We conduct both automatic and manual evaluations. All models trained on parallel data outperform the state-of-the-art unsupervised models by a large margin. This suggests that our novel datasets can boost the performance of detoxification systems.",
}
For any questions please contact Daryna Dementieva via email.