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Update README.md
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README.md
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@@ -13,7 +13,9 @@ LegalBERTPT-br is a trained sentence embedding using SimCSE, a contrastive learn
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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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# 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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