In the context of AI, what does NLG stand for?

Natural Language Generation, often abbreviated as NLG, refers to a subfield of artificial intelligence that focuses on the automatic generation of human language from structured data. It involves the use of algorithms and models to convert numerical data or other types of information into a natural human-readable format, enabling computers to create coherent and contextually relevant text.

NLG is commonly used in applications such as automated report generation, chatbots, and content creation systems. By leveraging NLG, businesses can convert data analytics into narratives that are easier for humans to understand, thus facilitating better decision-making and communication.

The other options, while they may seem plausible, do not accurately represent the established terminology used in the AI domain. For example, Neural Language Graph and Narrow Language Guidance do not correspond to widely recognized concepts in natural language processing. Numeric Language Generation is not a standard term, as NLG encompasses much broader capabilities than just numeric data. Thus, NLG specifically refers to the generation of natural language, making it the correct choice.