We test the GPT3 language model in zero- and few-shot acquisition of lexico-semantic knowledge in Portuguese, with simple instruction prompts, and compare it with a BERT-based approach. Results are assessed in two test sets: TALES and the Portuguese translation of BATS. GPT3 outperforms BERT in all relations, with the few-shot approach being the best overall and for the majority of relations. Scores in both datasets further suggest that, despite their different creation approaches, they are equally suitable for this kind of evaluation.