LlamaIndex 为 LlamaParse Extract 新增逐字段 Grounded Confidence 置信度评分

评分覆盖 bool、int、float 等基础类型（数值无需限定范围）和自由文本抽取，每个抽取值还附带指回原文位置的 bounding box。开发者可以设置阈值，让高置信度结果自动通过，低置信度结果转给人工审核。

该功能已在 Cost Effective、Agentic 和 Agentic Plus 三档方案上提供，文档见 developers.llamaindex.

ai。

with jev, everyone is understanding the importance of calibrated confidence scores for discrete decision making we've taken that approach one-step further and created grounded confidence scores for general schema-guided document extraction: ✅ this includes primitive types like bool, int, and float. the numbers don't have to be bounded ✅ this also includes free-form text extraction ✅ each extracted value also carries a bounding box directly back into the source document calibrated confidence scores are extremely important for human review. By setting a threshold, you can let a human reviewer audit the lower confidence values while automating the extraction of higher confidence values. If you have needs for large scale doc extraction, come check it out: developers.llamaindex.ai/llamaparse/ext… Sign up to LlamaParse here: cloud.llamaindex.ai

本条情报归属 AITOP「产品」核心栏目，重点聚焦北美前沿实验室与硅谷科技巨头。在跨区域产业观察坐标中，该动态直接关联「AI 开发者工具链、Coding Agent 与工程化实践」研究主线，反映出当前技术演进与商业落地的最新风向。涉及核心实体与技术议题包括：LlamaIndex、LlamaParse、文档抽取、置信度校准，读者可通过下方标签进入对应专题页查阅历史脉络与关联对比。

信源核验说明：本文原始线索采编自「Jerry Liu」（@jerryjliu0），经 AITOP 多维评分管线结构化提炼。