Abstract: A method and Graphic User Interface (GUI) system of data analysis for training a discriminative machine learning model are provided. One or more sets of data are provided to a large language model (LLM) for a predefined task with or without prompts provided by a user; the results output by the LLM is compared with a set of initial human-supplied ground truth data generated by the user to produce performance metrics, the user may provide or update one or more prompts for the LLM based on the performance metrics till the performance metrics reach a threshold. The set of initial human-supplied ground truth data and the results of the LLM can be used to train a discriminative machine learning model.