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---
dataset_info:
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 features:
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 - name: label
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 dataset_size: 1166302940.7979615
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configs:
- config_name: journalistic
 data_files:
 - split: train
 path: journalistic/train-*
 - split: valid
 path: journalistic/valid-*
 - split: test
 path: journalistic/test-*
- config_name: legal
 data_files:
 - split: train
 path: legal/train-*
 - split: valid
 path: legal/valid-*
 - split: test
 path: legal/test-*
- config_name: literature
 data_files:
 - split: train
 path: literature/train-*
 - split: valid
 path: literature/valid-*
 - split: test
 path: literature/test-*
- config_name: politics
 data_files:
 - split: train
 path: politics/train-*
 - split: valid
 path: politics/valid-*
 - split: test
 path: politics/test-*
- config_name: social_media
 data_files:
 - split: train
 path: social_media/train-*
 - split: valid
 path: social_media/valid-*
 - split: test
 path: social_media/test-*
- config_name: web
 data_files:
 - split: train
 path: web/train-*
 - split: valid
 path: web/valid-*
 - split: test
 path: web/test-*
---
# PtBrVId
**PtBrVId** is a Portuguese Variety Identification corpus, built by combining pre-existing datasets originally created for different NLP tasks and released under permissive licenses.
Our goal is to provide a large, diverse, and multi-domain resource for studying and improving automatic identification of **European Portuguese (PT-PT)** and **Brazilian Portuguese (PT-BR)**.
---
## 📚 Data Sources
The corpus is composed of datasets from various domains, each selected to ensure (as much as possible) mono-variety content. The current release is silver-labeled and unsupervised, meaning that we cannot fully guarantee that all documents are strictly mono-variety. A future version will include a refined annotation schema with both automatic and manual verification.
<p align="center">
 <table>
 <tr>
 <th>Domain</th>
 <th>Variety</th>
 <th>Dataset</th>
 <th>Original Task</th>
 <th># Docs</th>
 <th>License</th>
 <th>Silver Labeled</th>
 </tr>
 <tr>
 <td rowspan="5">Literature</td>
 <td rowspan="3">PT-PT</td>
 <td><a href="http://arquivopessoa.net/">Arquivo Pessoa</a></td>
 <td>-</td>
 <td>~4k</td>
 <td>CC</td>
 <td>✔</td>
 </tr>
 <tr>
 <td><a href="https://www.gutenberg.org/ebooks/bookshelf/99">Gutenberg Project</a></td>
 <td>-</td>
 <td>6</td>
 <td>CC</td>
 <td>✔</td>
 </tr>
 <tr>
 <td><a href="https://www.clul.ulisboa.pt/recurso/corpus-de-textos-literarios">LT-Corpus</a></td>
 <td>-</td>
 <td>56</td>
 <td>ELRA END USER</td>
 <td>✘</td>
 </tr>
 <tr>
 <td rowspan="2">PT-BR</td>
 <td><a href="https://www.kaggle.com/datasets/rtatman/brazilian-portuguese-literature-corpus">Brazilian Literature</a></td>
 <td>Author Identification</td>
 <td>81</td>
 <td>CC</td>
 <td>✘</td>
 </tr>
 <tr>
 <td>LT-Corpus</td>
 <td>-</td>
 <td>8</td>
 <td>ELRA END USER</td>
 <td>✘</td>
 </tr>
 <tr>
 <td rowspan="2">Politics</td>
 <td>PT-PT</td>
 <td><a href="http://www.statmt.org/europarl/">Koehn (2005) Europarl</a></td>
 <td>Machine Translation</td>
 <td>~10k</td>
 <td>CC</td>
 <td>✘</td>
 </tr>
 <tr>
 <td>PT-BR</td>
 <td>Brazilian Senate Speeches<sup>1</sup></td>
 <td>-</td>
 <td>~5k</td>
 <td>CC</td>
 <td>✔</td>
 </tr>
 <tr>
 <td rowspan="2">Journalistic</td>
 <td>PT-PT</td>
 <td><a href="https://www.linguateca.pt/CETEMPublico/">CETEM Público</a></td>
 <td>-</td>
 <td>1M</td>
 <td>CC</td>
 <td>✘</td>
 </tr>
 <tr>
 <td>PT-BR</td>
 <td><a href="https://www.linguateca.pt/CETEMFolha/">CETEM Folha</a></td>
 <td>-</td>
 <td>272k</td>
 <td>CC</td>
 <td>✘</td>
 </tr>
 <tr>
 <td rowspan="3">Social Media</td>
 <td>PT-PT</td>
 <td><a href="https://www.aclweb.org/anthology/2021.ranlp-1.37/">Ramalho (2021)</a></td>
 <td>Fake News Detection</td>
 <td>2M</td>
 <td>MIT</td>
 <td>✔</td>
 </tr>
 <tr>
 <td rowspan="2">PT-BR</td>
 <td><a href="https://www.aclweb.org/anthology/2022.lrec-1.322/">Vargas (2022)</a></td>
 <td>Hate Speech Detection</td>
 <td>5k</td>
 <td>CC-BY-NC-4.0</td>
 <td>✘</td>
 </tr>
 <tr>
 <td><a href="https://www.aclweb.org/anthology/2021.wlp-1.72/">Cunha (2021)</a></td>
 <td>Fake News Detection</td>
 <td>2k</td>
 <td>GPL-3.0</td>
 <td>✔</td>
 </tr>
 <tr>
 <td>Web</td>
 <td>BOTH</td>
 <td><a href="https://www.aclweb.org/anthology/2020.lrec-1.451/">Ortiz-Suarez (2020)</a></td>
 <td>-</td>
 <td>10k</td>
 <td>CC</td>
 <td>✔</td>
 </tr>
 </table>
</p>
<p align="center"><em>Table 1: PtBrVId data sources and metadata.</em></p>
<sup>1</sup> The **Brazilian Senate Speeches** dataset was created by the authors through web crawling of the Brazilian Senate website and is available on [Hugging Face](https://huggingface.co/).
A raw version of the dataset is available [here](https://huggingface.co/datasets/liaad/PtBrVId-Raw).
---
## 🛠 Annotation & Preprocessing
### Annotation
We selected data sources known to contain primarily mono-variety Portuguese texts. While this approach helps ensure quality, this **first release** is entirely unsupervised. A planned **v2** will introduce a hybrid annotation strategy combining automated labeling and manual review.
### Preprocessing Pipeline
To standardize and clean the data, we applied the following steps:
1. **Remove NaN values**.
2. **Remove empty documents**.
3. **Remove duplicate documents**.
4. Apply the [`clean-text`](https://github.com/jfilter/clean-text) library to strip non-relevant content for variety identification.
5. Remove outlier documents with lengths below `Q1 - 1.5 × IQR` or above `Q3 + 1.5 × IQR`, where `Q1` and `Q3` are the first and third quartiles, and `IQR` is the interquartile range.
---
## 📖 Citation
If you use this corpus, please cite:
```bibtex
@article{Sousa_Almeida_Silvano_Cantante_Campos_Jorge_2025,
 title={Enhancing Portuguese Variety Identification with Cross-Domain Approaches},
 journal={Proceedings of the AAAI Conference on Artificial Intelligence},
 volume={39},
 number={24},
 pages={25192--25200},
 year={2025},
 doi={10.1609/aaai.v39i24.34705},
 author={Sousa, Hugo and Almeida, Rúben and Silvano, Purificação and Cantante, Inês and Campos, Ricardo and Jorge, Alípio}
}