CoolFace
Datasetpublic

amalia-llm/PT-Culture_Data

Portuguese Cultural SFT Dataset A supervised fine-tuning dataset for European Portuguese (PT-PT) cultural knowledge, built to teach models the traditions, figures, places, and expressions of Portuguese culture. The dataset contains 216,832 examples across two versions in conversational SFT format, organised into ten cultural domains: Domain v1 (95,815) v2 (121,017) Total Personalities 36,370 62,788 99,158 Audiovisual 15,786 26,857 42,643 Heritage 8,020… See the full description on the dataset page: https://huggingface.co/datasets/amalia-llm/PT-Culture_Data.

sourceHugging Faceapache-2.0updated 2mo agoView on Hugging Face
1likes54downloads
Dataset Card

<div align="center">

<img width="400px" src="https://github.com/AMALIA-LLM/amalia-llm.github.io/blob/main/source/_static/logo/logo-color-black.png?raw=true">

![AMALIA](https://amaliallm.pt/) ![Paper](https://aclanthology.org/2026.propor-1.38/) ![Data](https://huggingface.co/collections/amalia-llm/amalia-lm-eval/) ![Main Repo](https://github.com/AMALIA-LLM/AMALIA) ![Eval Repo](https://github.com/AMALIA-LLM/amalia-lm-eval)

</div>

Portuguese Cultural SFT Dataset

A supervised fine-tuning dataset for European Portuguese (PT-PT) cultural knowledge, built to teach models the traditions, figures, places, and expressions of Portuguese culture.

The dataset contains 216,832 examples across two versions in conversational SFT format, organised into ten cultural domains:

Domainv1 (95,815)v2 (121,017)Total
Personalities36,37062,78899,158
Audiovisual15,78626,85742,643
Heritage8,02010,35018,370
Sports3968,1408,536
Geography11,9474,12116,068
Literature3,1994,8018,000
Gastronomy2,4923,0775,569
Proverbs16,178—16,178
Festivals7504541,204
Holidays6774291,106
Total95,815121,017216,832

The data spans seven task types: Verification, short and long question-answering, cultural-context reasoning, entity comparison, multi-turn dialogue (persona-diversified) and proverb meaning explanation.

Two files are available: culture_data_sft.jsonl (v1) and culture_data_sft_v2.jsonl (v2). For training on all data, use both files combined.

This dataset is provided as part of the AMALIA project and is included in the data mix used to post-train the AMALIA model.


Citation

If you use this dataset or AMALIA in your work, please cite:

bibtex
@inproceedings{simplicio-etal-2026-amalia,
    title = "{AMALIA}: A Fully Open Large Language Model for {E}uropean {P}ortuguese",
    author = "Simpl{{\'i}}cio, Afonso and Vinagre, Gon{{\c{{c}}}}alo and Ramos, Miguel Moura and Tavares, Diogo and Ferreira, Rafael and Attanasio, Giuseppe and Alves, Duarte M. and Calvo, In{{\^e}}s and Vieira, In{{\^e}}s and Guerra, Rui and Furtado, James and Canaverde, Beatriz and Paulo, Iago and Ramos, Vasco and Gl{{\'o}}ria-Silva, Diogo and Faria, Miguel and Treviso, Marcos and Gomes, Daniel and Gomes, Pedro and Semedo, David and Martins, Andr{{\'e}} and Magalh{{\~a}}es, Jo{{\~a}}o",
    booktitle = "Proceedings of the 17th International Conference on Computational Processing of {{P}}ortuguese ({{PROPOR}} 2026) - Vol. 1",
    month = apr,
    year = "2026",
    address = "Salvador, Brazil",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2026.propor-1.38/",
    pages = "380--391",
    isbn = "979-8-89176-387-6"
}

@misc{simplicio2026amaliatechnicalreportfully,
    title = {AMALIA Technical Report: A Fully Open Source Large Language Model for European Portuguese},
    author = {Afonso Simplício and Gonçalo Vinagre and Miguel Moura Ramos and Diogo Tavares and Rafael Ferreira and Giuseppe Attanasio and Duarte M. Alves and Inês Calvo and Inês Vieira and Rui Guerra and James Furtado and Beatriz Canaverde and Iago Paulo and Vasco Ramos and Diogo Glória-Silva and Miguel Faria and Marcos Treviso and Daniel Gomes and Pedro Gomes and David Semedo and André Martins and João Magalhães},
    year = {2026},
    eprint = {2603.26511},
    archivePrefix = {arXiv},
    primaryClass = {cs.CL},
    url = {https://arxiv.org/abs/2603.26511}
}