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--- |
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language: pt |
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license: mit |
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tags: |
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- sentence-transformers |
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--- |
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# LegalBERTPT-br |
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LegalBERTPT-br is a trained sentence embedding using SimCSE, a contrastive learning framework, coupled with the Portuguese pre-trained language model named [BERTimbau](https://huggingface.co/neuralmind/bert-base-portuguese-cased). |
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# Corpora |
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– From [this site](https://www2.camara.leg.br/transparencia/servicos-ao-cidadao/participacao-popular), we used the column `Conteudo` with 215,713 comments. We removed the comments from PL 3723/2019, PEC 471/2005, and Hashtag Corpus, in order to avoid bias. |
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– From [this site](https://www2.camara.leg.br/transparencia/servicos-ao-cidadao/participacao-popular), we also used 147,008 bills. From these projects, we used the summary field named `txtEmenta` and the project core text named `txtExplicacaoEmenta`. |
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– From Political Speeches, we used 462,831 texts, specifically, we used the columns: `sumario`, `textodiscurso`, and `indexacao`. |
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These corpora were segmented into sentences and concatenated, producing 2,307,426 sentences. |
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# Citing and Authors |
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If you find this model helpful, feel free to cite our publication [Evaluating Topic Models in Portuguese Political Comments About Bills from Brazil’s Chamber of Deputies](https://link.springer.com/chapter/10.1007/978-3-030-91699-2_8): |
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```bibtex |
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@inproceedings{bracis, |
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author = {Nádia Silva and Marília Silva and Fabíola Pereira and João Tarrega and João Beinotti and Márcio Fonseca and Francisco Andrade and André Carvalho}, |
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title = {Evaluating Topic Models in Portuguese Political Comments About Bills from Brazil’s Chamber of Deputies}, |
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booktitle = {Anais da X Brazilian Conference on Intelligent Systems}, |
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location = {Online}, |
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year = {2021}, |
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keywords = {}, |
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issn = {0000-0000}, |
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publisher = {SBC}, |
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address = {Porto Alegre, RS, Brasil}, |
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url = {https://sol.sbc.org.br/index.php/bracis/article/view/19061} |
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} |
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``` |
