  We investigate the effectiveness of GPT-3.5 and GPT-4, two large language
models, as Grammatical Error Correction (GEC) tools for Brazilian Portuguese
and compare their performance against Microsoft Word and Google Docs. We
introduce a GEC dataset for Brazilian Portuguese with four categories: Grammar,
Spelling, Internet, and Fast typing. Our results show that while GPT-4 has
higher recall than other methods, LLMs tend to have lower precision, leading to
overcorrection. This study demonstrates the potential of LLMs as practical GEC
tools for Brazilian Portuguese and encourages further exploration of LLMs for
non-English languages and other educational settings.
