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

TL;DR

This paper presents novel question answering systems in Portuguese focused on environmental topics in Brazil, combining retrieval and language models to improve social awareness about ecological issues.

Contribution

Introduces innovative QA architectures combining BM25 and PTT5 for Portuguese environmental questions, with new datasets and applications.

Findings

Achieved an F1-score of 36.2 with the best model.

Developed QA systems tailored for Portuguese ecological content.

Provided resources and methods not previously available in the literature.

Abstract

The challenge of climate change and biome conservation is one of the most pressing issues of our time - particularly in Brazil, where key environmental reserves are located. Given the availability of large textual databases on ecological themes, it is natural to resort to question answering (QA) systems to increase social awareness and understanding about these topics. In this work, we introduce multiple QA systems that combine in novel ways the BM25 algorithm, a sparse retrieval technique, with PTT5, a pre-trained state-of-the-art language model. Our QA systems focus on the Portuguese language, thus offering resources not found elsewhere in the literature. As training data, we collected questions from open-domain datasets, as well as content from the Portuguese Wikipedia and news from the press. We thus contribute with innovative architectures and novel applications, attaining an F1-score of 36.2 with our best model.