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.

Abstract: A system comprising: an input receiving an input document comprising text data and graphical data distinguishing hierarchically first and second portion of the text data; a display displaying said input document; a user interface allowing a user to add, in superposition with the displayed input document, boundary markers visually bounding said first and second text portions; and a processor arranged for, using the boundary markers added to the displayed input document, training a layout data analysis model to determine, in a further input document having further text data, if graphical data distinguishes hierarchically first and second portions of the further text data to display automatically boundary markers visually bounding said first and second portions of said further text data; the user interface allowing said user to correct the boundary markers displayed by the layout analysis model and the processor training the layout data analysis model using the corrected boundary markers.

Abstract: The present invention is a system and method for tracking evidence objects and sharing evidence data between agencies. The system and method may also record evidence object locations and the agency or persons responsible for the evidence objects in order to build or maintain a chain of custody record for an evidence object.