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--- |
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annotations_creators: |
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- no-annotation |
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language: |
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- pt |
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license: |
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- other |
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multilinguality: |
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- monolingual |
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pretty_name: ParlamentoPT |
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size_categories: |
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- 1M<n<10M |
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source_datasets: |
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- original |
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task_categories: |
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- text-generation |
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- fill-mask |
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task_ids: |
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- language-modeling |
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- masked-language-modeling |
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tags: |
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- parlamentopt |
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- parlamento |
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- parlamento-pt |
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- albertina-pt* |
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- albertina-ptpt |
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- albertina-ptbr |
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- fill-mask |
|
- bert |
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- deberta |
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- portuguese |
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- encoder |
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- foundation model |
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--- |
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|
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# Dataset Card for ParlamentoPT |
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### Dataset Summary |
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The ParlamentoPT is a **Portuguese** language data set obtained by collecting publicly available documents containing transcriptions of debates in the Portuguese Parliament. |
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The data was collected from the Portuguese Parliament portal in accordance with its [open data policy](https://www.parlamento.pt/Cidadania/Paginas/DadosAbertos.aspx). |
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This dataset was collected with the purpose of creating the [Albertina-PT*](https://huggingface.co/PORTULAN/albertina-ptpt) language model, and it serves as training data for model development. |
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The development of the model is a collaborative effort between the University of Lisbon and the University of Porto in Portugal |
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</br> |
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# Citation |
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When using or citing this data set, kindly cite the following [publication](https://arxiv.org/abs/2305.06721): |
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``` latex |
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@misc{albertina-pt, |
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title={Advancing Neural Encoding of Portuguese |
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with Transformer Albertina PT-*}, |
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author={João Rodrigues and Luís Gomes and João Silva and |
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António Branco and Rodrigo Santos and |
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Henrique Lopes Cardoso and Tomás Osório}, |
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year={2023}, |
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eprint={2305.06721}, |
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archivePrefix={arXiv}, |
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primaryClass={cs.CL} |
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} |
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``` |
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<br> |
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# Acknowledgments |
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The research reported here was partially supported by: PORTULAN CLARIN—Research Infrastructure for the Science and Technology of Language, |
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funded by Lisboa 2020, Alentejo 2020 and FCT—Fundação para a Ciência e Tecnologia under the |
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grant PINFRA/22117/2016; research project ALBERTINA - Foundation Encoder Model for Portuguese and AI, funded by FCT—Fundação para a Ciência e Tecnologia under the |
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grant CPCA-IAC/AV/478394/2022; innovation project ACCELERAT.AI - Multilingual Intelligent Contact Centers, funded by IAPMEI, I.P. - Agência para a Competitividade e Inovação under the grant C625734525-00462629, of Plano de Recuperação e Resiliência, call RE-C05-i01.01 – Agendas/Alianças Mobilizadoras para a Reindustrialização; and LIACC - Laboratory for AI and Computer Science, funded by FCT—Fundação para a Ciência e Tecnologia under the grant FCT/UID/CEC/0027/2020. |
