Semantic models are tools used in natural language processing and computational linguistics to represent the meaning of words, phrases, or entire texts. These models aim to capture the relationships between different words and concepts in order to better understand and interpret language. Semantic models can be based on various techniques, including vector space models, graph-based models, and neural networks. These models are used in a variety of applications, such as information retrieval, machine translation, and sentiment analysis. They play a crucial role in enabling computers to understand and generate human language.