Generation of synthetic question-answer pairs using a document classifier and classification explainer

A computing apparatus comprising memory and one or more processors communicatively coupled to the memory, the one or more processors configured to:

• generate one or more predicted label indicators associated with a textual dataset based on inputting the textual dataset to a dataset classification predicting machine learning model;
• generate one or more prediction score indicators associated with one or more prediction explanation indicators based on inputting the textual dataset and the one or more predicted label indicators to a classification explanation predicting machine learning model;
• generate one or more structured label-explanation datasets based on the one or more predicted label indicators, the one or more prediction explanation indicators, and the one or more prediction score indicators;
• generate one or more synthetic question-answer (QA) training datasets based on the one or more structured label-explanation datasets and a prediction score threshold;
• generate a prediction output using one or more QA machine learning models that are trained based on the synthetic QA training datasets;
• and
• initiate the performance of one or more prediction-based operations based on the prediction output.

One or more non-transitory computer-readable storage media including instructions that, when executed by one or more processors, cause the one or more processors to:

• generate one or more predicted label indicators associated with a textual dataset based on inputting the textual dataset to a dataset classification predicting machine learning model;
• generate one or more prediction score indicators associated with one or more prediction explanation indicators based on inputting the textual dataset and the one or more predicted label indicators to a classification explanation predicting machine learning model;
• generate one or more structured label-explanation datasets based on the one or more predicted label indicators, the one or more prediction explanation indicators, and the one or more prediction score indicators;
• generate one or more synthetic question-answer (QA) training datasets based on the one or more structured label-explanation datasets and a prediction score threshold;
• generate a prediction output using one or more QA machine learning models that are trained based on the synthetic QA training datasets;
• and
• initiate the performance of one or more prediction-based operations based on the prediction output.