The honest answer is between 500 and 500,000, and which end you are at depends almost entirely on whether you are teaching behaviour or coverage. Fortunately the question is cheap to answer empirically, and the procedure at the end of this page is worth more than any number.
Why the number is unanswerable as asked
“How many examples” conflates two quantities that behave completely differently. One is how many examples it takes for the model to learn the pattern — the output shape, the register, the decision rule. The other is how many it takes to cover the input space — every document type, every edge case, every locale.
The first number is startlingly small, because the base model already knows how to write JSON and how to be terse; you are selecting an existing behaviour, not installing one. The second number is bounded by the diversity of your inputs and has nothing to do with the model at all. A task with four input shapes needs a fraction of the data of a task with four hundred, at identical difficulty.
Three published anchors
