Semantic representations are structured ways to capture the meaning of information. They help in understanding how different concepts relate to each other. For example, in natural language processing, semantic representations can be used to analyze sentences and extract their meanings, making it easier for machines to understand human language. These representations often use graphs or networks, where nodes represent concepts and edges represent relationships. This approach is useful in various fields, including artificial intelligence and linguistics, as it allows for better communication between humans and machines, enhancing tasks like information retrieval and question answering.