This paper presents the Dunamu-ml’s submission to the AVERITEC shared task of the 7th the Fact Extraction and VERification (FEVER) workshop. The task focused on discriminating whether each claim is a fact or not. Our method is powered by the combination of an LLM and a non-parametric lexicon-based method (i.e. BM25). Essentially, we augmented the list of evidences containing the query and the corresponding answers using an powerful LLM, then, retrieved the relative documents using the generated evidences. As such, our method made a great improvement over the baseline results, achieving 0.33 performance gain over the baseline in AveriTec score.