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---
# 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.
Table 1: PtBrVId data sources and metadata.
1 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, AlÃpio}
}