Titlebook: Computational Processing of the Portuguese Language; 15th International C Vládia Pinheiro,Pablo Gamallo,Hugo Pinto Conference proceedings 2

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https://doi.org/10.1007/978-3-658-38350-3nt of health crises. In this context, automatic fake news classification systems have been profitably created to tackle this problem. These systems require balanced corpus to be used as training data for the machine learning models. In this article, we present a flexible corpus of fake news in Portu

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Standortplanung in der Katastrophenlogistikhow these models, trained with a masked language modeling objective, encode syntactic knowledge. To do so, we created a new dataset including test instances of number (subject-verb), gender (subject-predicative adjective), and person (subject-inflected infinitive) agreement. This dataset was used to

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