Python offers efficient methods for utilizing semantic similarity to determine a word's relevance to a text sentence. Words can be numerically scored by using techniques such as TF-IDF, word embeddings, and Transformer models. In "I want to eat," for instance, the word "food" would score higher than "house," demonstrating how useful these methods are for analyzing textual data.