What type of data is being used by an engineer who categorizes news articles into topics with predefined labels?

The scenario describes an engineer categorizing news articles into topics using predefined labels. This process involves associating each news article with a specific label that indicates its category, such as sports, politics, or technology.

In this context, the type of data being used is labeled data. Labeled data refers to datasets that include input data paired with the correct output. In the case of the news articles, each article (input) is assigned a category (output) based on the predefined labels. This labeled data is crucial for supervised learning algorithms, which learn to predict the category of new, unseen articles based on the patterns learned from the labeled examples.

Training data and test data could be relevant, as labeled data is often divided into these subsets for model training and evaluation. However, the key aspect in this question is the presence of predefined labels, which specifically defines the data as labeled. Unlabeled data, in contrast, would not have any such labels or categories available for reference during the categorization process.