The need of indexing biomedical papers with the MeSH is incessantly growing and automated approaches are constantly evolving. Since 2013, the BioASQ challenge has been promoting those evolutions by proposing datasets and evaluation metrics. In this paper, we present our system, USI, and how we adapted it to participate to this challenge this year. USI is a generic approach, which means it does not directly take into account the content of the document to annotate. The results lead us to the conclusion that methods that solely rely on semantic annotations available in the corpus can already perform well compared to NLP-based approaches as our results always figure in the top ones.