LlamaIndex发布 ExtractBench Pro
LlamaIndex 发布 ExtractBench Pro,作为两个月前推出的 ExtractBench 的扩展,专门覆盖真实客户文档中未被原基准覆盖的长尾难题。新基准共 100 份文档,全部由确定性流程结合种子与配置合成,并分为文档惯例、内部词汇、内部计数规则、绘制关系、文档内图表和超长图表纸六类挑战。LlamaIndex 称其用 12 个系统进行了测试,包括 4 个抽取 API、5 个编码智能体和三个档位的 LlamaExtract,并新增“Value F1 达到 100% 的文档比例”这一指标;这些结果由厂商自行运行,尚无独立复现。
LlamaIndex 表示,尽管原 ExtractBench 的分数正接近饱和,文档抽取仍未解决,并称刚性流水线在 ExtractBench Pro 上表现吃力,而配备合适工具的智能体系统能够适应。
Two months ago, we released ExtractBench to measure and improve schema-based document extraction. What we learned from it has accelerated our research: in the LlamaExtract v2.5 release, even our lowest-cost tier scores above 93% value F1.
But the benchmark also had blind spots. Some real customers brought complex documents and schemas that the original 370 ExtractBench documents never covered. This is the long tail of document extraction. It’s why extraction remains unsolved, even as scores on ExtractBench climb toward saturation.
Today we’re releasing ExtractBench Pro, an extension built from those real long-tail documents. It covers six new challenges, each drawn from ways that real customers broke our assumptions. In the samples below, you’ll find values that appear only in intricate charts, rules on one page that change the meaning of another, dense domain jargon, chaotic layouts, and more. Rigid pipelines struggle on ExtractBench Pro, but agentic systems with the right tools can adapt.
