Relation Extraction is a natural language processing task that involves identifying and classifying relationships between entities in a text. For example, in the sentence "Barack Obama was born in Hawaii," the entities are Barack Obama and Hawaii, and the relationship is "born in." This process helps in organizing information and making it easier to understand the connections between different pieces of data. The goal of Relation Extraction is to create structured data from unstructured text, which can be useful for various applications like knowledge graph construction, information retrieval, and question answering. By accurately identifying relationships, systems can better interpret and utilize the information contained in large volumes of text.