Recall
Of the things it should have found, how many it actually found.
The fuller definition
Recall is the fraction of expected positive results that a system finds: true positives divided by true positives plus false negatives.
The reference set has ten relevant events. Six are found, four are missed, and two additional returned items are unsupported. This example measures extraction, not every aspect of a legal work product.
A concrete example
If ten relevant events exist and the extraction finds six, recall is 6/10, or 60%.
The distinction that matters
Recall depends on a credible reference set; unknown missing events cannot be counted simply by inspecting returned rows.
Related terms
Where it is taught
Test an AI workflow on work you can assessSource and further reading
Anthropic · Evaluating AI agentsThe definition and example are written for this library. The link gives background, official documentation or legal authority as labelled. Legal scope depends on the jurisdiction and current text; product features depend on release and settings.