Which feature allows users to explore a dataset’s verbatims and apply labels and entities?

The feature that allows users to explore a dataset's verbatims and apply labels and entities is the Exploration capability. This feature is designed to facilitate a deeper understanding of the data by providing tools to analyze and interpret verbatim responses, such as text entries or free text input.

In this context, the capability to explore involves navigating through the dataset's contents, identifying key themes or specific pieces of information, and applying various labels or tags to these data points. This process is crucial for tasks like sentiment analysis, topic modeling, or any form of natural language processing where extracting structured information from unstructured text is necessary.

The other features, while important, serve different functions. The "Train" option typically relates to the model training phase, where algorithms learn from labeled data to improve their accuracy. "Discover" can refer to the process of uncovering patterns or trends within a dataset but does not specifically address handling verbatims. "Validation" usually involves checking the accuracy of a model or its outputs rather than interacting with the dataset directly. Therefore, the "Explore" feature is uniquely positioned to meet the needs of examining verbatims and applying insightful categorization to them.