This paper proposes LaSSI, a Natural Language Processing (NLP) pipeline contextualising verified Artificial Intelligence (AI) by transforming text via Montague Grammars (MGs). We are approaching from the point-of-view of graphs and logic, in which we achieve explainable sentence similarity in terms of Knowledge Base (KB) expansion and possible worlds semantics. Experiments in the present paper excel current state-of-the-art, Graph Retrieval-Augmented Generation (RAG)-based technologies, through a novel method surpassing vector-based and graph-based sentence similarity metrics.