Agents
confidence scores only matter if they help you decide what to automate. for document extraction, that usually means knowing how much work yo…
confidence scores only matter if they help you decide what to automate. for document extraction, that usually means knowing how much work you can safely accept at a given precision target. in our late
confidence scores only matter if they help you decide what to automate. for document extraction, that usually means knowing how much work you can safely accept at a given precision target. in our latest post, we look at confidence scoring through that lens, including: ✅️ confidence cutoffs ✅️ precision vs. recall ✅️ score coverage ✅️ score granularity ✅️ human review volume using ExtractBench, we compare how different extraction systems perform after confidence filtering. at a 97% precision target, LlamaParse Agentic Plus reached 66.48% recall on expected fields after filtering. the useful part of a confidence score isn’t the number itself. it’s whether you can use it to control automation and review in production. 👉️ read the full post: https://www.llamaindex.ai/blog/what-makes-an-extraction-confidence-score-useful Media
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- Parsing a document accurately is one thing. Proving where every value came from is another. When a compliance team reviews an AI extraction,…
Source: Jerry Liu (X) | 2026-09-24