Semantic Role Labeling (SRL) is a natural language processing technique that identifies the roles played by words in a sentence. It helps determine who did what, to whom, and under what circumstances. For example, in the sentence "The cat chased the mouse," SRL identifies the cat as the agent and the mouse as the patient. By analyzing the structure of sentences, SRL assigns labels to different components, making it easier for machines to understand meaning. This process is crucial for various applications, including information extraction, question answering, and machine translation, enhancing the ability of systems to comprehend human language.