Dataset clustering via language model prompts

A computer-implemented method comprising:

• receiving a dataset;
• receiving a natural language prompt that includes an instruction to generate, from the dataset, at least one of:
• a category representing a cluster according to a particular use case, a description that summarizes the cluster of the particular use case, or a label representing a name of the cluster;
• in response to the receiving of the natural language prompt, generating, via a machine learning model, at least one of:
• the category, the description, or the label;
• based at least in part on the generating, assigning the dataset to the label;
• and
• based at least in part on the assigning, causing presentation, at a user device, of an indication of the assignment of the dataset to the label.

One or more computer storage media having computer-executable instructions embodied thereon that, when executed, by one or more processors, cause the one or more processors to perform operations comprising:

• receiving a plurality of datasets, each dataset including a set of natural language characters;
• for each dataset, providing a representation of the set of natural language characters as a first input into a machine learning model, wherein the machine learning model generates a plurality of natural language summaries based on the set of natural language characters for each dataset;
• parsing the plurality of natural language summaries into two or more batches;
• providing each batch as a second input into the machine learning model, wherein the machine learning model generates and updates at least one label for at least one batch of the two or more batches;
• based at least in part on the generating and the updating of the at least one label, assigning each dataset to a respective label of the at least one label;
• and
• based at least in part on the assigning of each dataset to the respective label, causing presentation, at a user device, of an indication of the assignment of each dataset to the respective label.