ServiceNow, Inc.
ENSEMBLE SCORING SYSTEM FOR A NATURAL LANGUAGE UNDERSTANDING (NLU) FRAMEWORK

Abstract:

A natural language understanding (NLU) framework includes an ensemble scoring system designed to receive indicators determined by various systems of the NLU framework when inferencing a user utterance. The ensemble scoring system uses the received indicators, along with a set of ensemble scoring weights, to determine a respective ensemble score for each artifact of the utterance identified during inference. For example, segmentations provided by a lookup source system may be used to boost scores of intent and/or entities identified during a meaning search operation of a NLU system. The NLU framework may also include an ensemble scoring weight optimization subsystem that automatically determines optimized ensemble scoring weight values from labeled training data using an optimization plugin. Accordingly, the NLU framework enables these indicators to be suitably weighted and combined to provide a desired level of performance (e.g., computational resource consumption, precision, recall) of the NLU framework during operation.