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The challenge of climate change and biome conservation is one of the mostpressing issues of our time - particularly in Brazil, where key environmentalreserves are located. Given the availability of large textual databases onecological themes, it is natural to resort to question answering (QA) systemsto increase social awareness and understanding about these topics. In thiswork, we introduce multiple QA systems that combine in novel ways the BM25algorithm, a sparse retrieval technique, with PTT5, a pre-trainedstate-of-the-art language model. Our QA systems focus on the Portugueselanguage, thus offering resources not found elsewhere in the literature. Astraining data, we collected questions from open-domain datasets, as well ascontent from the Portuguese Wikipedia and news from the press. We thuscontribute with innovative architectures and novel applications, attaining anF1-score of 36.2 with our best model.

DEEPAG\'E: Answering Questions in Portuguese about the Brazilian Environment