Dataset Curation

Dataset curation is the process of collecting, filtering, labeling, and versioning examples used to evaluate, fine-tune, or benchmark an LLM application. In production LLMOps, curation draws from logged real queries, human-annotated responses, and synthetic data generated to cover edge cases not naturally present in traffic. Curated datasets must be deduped, balanced across difficulty levels and topics, and regularly refreshed to remain representative as user behavior evolves.