Recent research suggests that infants tend to add words to their vocabulary that are semantically related to other known words, though it is not clear why this pattern emerges. In this paper, we explore whether infants leverage their existing vocabulary and semantic knowledge when interpreting novel label–object mappings in real time. We initially identified categorical domains for which individual 24‐month‐old infants have relatively higher and lower levels of knowledge, irrespective of overall vocabulary size. Next, we taught infants novel words in these higher and lower knowledge domains and then asked if their subsequent real‐time recognition of these items varied as a function of their category knowledge. While our participants successfully acquired the novel label–object mappings in our task, there were important differences in the way infants recognized these words in real time. Namely, infants showed more robust recognition of high (vs. low) domain knowledge words. These findings suggest that dense semantic structure facilitates early word learning and real‐time novel word recognition. We measured novel word recognition in 24 month old children as a function of whether newly learned words came from relatively dense or sparse semantic categories. Results indicated that words were recognized more reliably when words came from dense categories. The findings suggest that young children recognize links between novel and known word meanings and leverage this knowledge during word learning.