Abstract: The present method extracts and correlates functional values and structural information from a worksheet data environment. The method extracts the functional values from the worksheet data environment. For each functional value, the method: extracts structural information provided in the worksheet data environment for the functional value, extracts data elements and structural information of the data elements onto which a function is executed to generate the functional value, interconnects the functional value with the corresponding structural information, interconnects the functional value with the data elements onto which the function is executed, and interconnects the structural information of the data elements onto which the function is executed to obtain the functional value.

Abstract: The present specification provides a method for training a machine learning model into a task-specific model. The method comprises steps of prompting a Large Language Model (LLM) to generate definitions and manifestations and a test data set for information elements related to a task. The method comprises inputting the list of information elements, the definitions and the manifestations in the machine learning model as structured learning parameters and label by the machine learning model an initial data set to generate a labelled data set. The method performs an adversarial augmentation loop on the labelled data set, the adversarial augmentation loop: identifying improper embeddings in the labelled data set, re-labelling the improper labels in the labelled data set and generating a task-specific data set. The method evaluates performance of the machine learning model trained with the task-specific data set by instructing the machine learning model to classify the test data set.

Abstract: The present computer system and method identify or infer a topic or an entity from unstructured data text, filter passages mentioning the topic and/or entity, and execute a Large Language Model (LLM) with the passages mentioning the topic for inferring at least one entity associated with the topic. The LLM may further infer a relationship between the topic and each of the at least one entity. The computer system and method further distil the topic, the at least one entity and the relationship therebetween into distilled inferred knowledge.