Case & CodeA FIELD GUIDE TO AI
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Intermediate

False negative

Also: false negatives

In plain words

Something the system missed that it should have found.

The fuller definition

A false negative is an item that meets the target condition but is missed or classified as negative.

A ten-event extraction test
FoundE01
FoundE02
FoundE03
FoundE04
FoundE05
FoundE06
MissedE07
MissedE08
MissedE09
MissedE10
Unsupported result AUnsupported result B
Precision: 6 / 8 = 75%Recall: 6 / 10 = 60%

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

A search omits a relevant email because it uses different wording from the query.

The distinction that matters

You need coverage checks or a reference set to discover omissions that are invisible in the returned output.

Related terms

Where it is taught

Test an AI workflow on work you can assess

Source and further reading

Anthropic · Evaluating AI agents

The 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.

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