LlamaIndex: use confidence scores to decide what to automate in extraction
llama_index · x · 2026-09-25
LlamaIndex published a post framing confidence scores through a practical lens: they only matter if they help you decide what to automate. For document extraction, that means knowing how much work you can safely accept at a given precision target. The post covers confidence cutoffs, precision vs. recall, score coverage, score granularity, and human review volume. Using ExtractBench, they compare extraction systems after confidence filtering: at a 97% precision target, LlamaParse Agentic Plus reached 66.48% recall on expected fields. The takeaway: a score's value is in controlling automation and review in production, not the number itself.
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