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Even though most of its energy generation comes from renewable sources,Brazil is one of the largest emitters of greenhouse gases in the world, due tointense farming and deforestation of biomes such as the Amazon Rainforest,whose preservation is essential for compliance with the Paris Agreement. Still,regardless of lobbies or prevailing political orientation, all government legalactions are published daily in the Brazilian Federal Official Gazette (BFOG, or"Di\'ario Oficial da Uni\~ao" in Portuguese). However, with hundreds of decreesissued every day by the authorities, it is absolutely burdensome to manuallyanalyze all these processes and find out which ones can pose seriousenvironmental hazards. In this paper, we present a strategy to composeautomated techniques and domain expert knowledge to process all the data fromthe BFOG. We also provide the Government Actions Tracker, a highly curateddataset, in Portuguese, annotated by domain experts, on federal government actsabout the Brazilian environmental policies. Finally, we build and compared fourdifferent NLP models on the classfication task in this dataset. Our best modelachieved a F1-score of $0.714 \pm 0.031$. In the future, this system shouldserve to scale up the high-quality tracking of all oficial documents with aminimum of human supervision and contribute to increasing society's awarenessof government actions.

Tracking environmental policy changes in the Brazilian Federal Official Gazette