From High Recall to High Utility: Dataset-Adaptive Post-Processing of LLM-Generated Customer Intents

Large language models can extract useful signals from heterogeneous enterprise data, but high-recall extraction often produces outputs that are duplicated, uneven in granularity, semantically overlapping, or too numerous for downstream systems and human reviewers to use effectively.