This article explores the mathematization of meaning and context in NLP through distributional semantics and contextualized word representations. — In this article, we uncover various methods used to ascertain the similarity between words and sentences, including lexical similarity, semantic similarity, syntactic similarity, machine learning methods, and hybrid approaches. However, our main focus lies on distributional similarity, a technique that analyzes the contextual patterns in which words or sentences appear.