Natural language generation (natural language processing) is the computational process of producing human-readable text from non-linguistic data or internal machine representations. As a core subfield of Natural Language Processing, it focuses on transforming structured information, knowledge bases, or other formal data sources into coherent, grammatically correct, and contextually appropriate natural language outputs. This process involves stages such as content determination, data-to-text structuring, and linguistic realization, serving to bridge the gap between machine understanding and human communication by enabling systems to articulate information, explanations, or responses in a form understandable to humans. Its significance lies in its role in applications requiring automated content creation, automated reporting, dialogue systems, and the verbalization of data insights.