What type of data is characterized by having been manually reviewed and tagged with categories such as "Billing Inquiry" or "Technical Support"?

The correct choice is labeled data because it specifically refers to datasets that have been annotated or tagged with meaningful categories that make them suitable for supervised learning tasks. In this context, having categories like "Billing Inquiry" or "Technical Support" demonstrates that human reviewers have assessed the data and provided categorical labels based on its content. This enables machine learning models to recognize patterns and make predictions based on the labeled examples.

In contrast, unlabeled data would consist of raw information without any human-generated tags, making it less useful for training supervised models directly. Structured data describes information that is organized in a predefined manner, such as within rows and columns in databases, but it doesn't explicitly indicate whether the data is labeled or not. Raw data refers to unprocessed information that hasn't been cleaned or transformed for analysis, again without any labels associated with it. Thus, labeled data is the most accurate term for the described scenario.