Structured Output

A structured extraction prompt for clean JSON output from unstructured text, notes, or documents.

Reviewed: 2026-03-18

Use this when you need reliable machine-readable output from free-form text and you want the model to stay inside a strict schema.

Prompt Template

Extract the information below and return valid JSON only.

Schema:
{schema}

Rules:
- If a field is missing, use null.
- Keep original wording where possible.
- Do not invent facts.
- Return one JSON object and nothing else.

Input:
{text}

Customize the variables before using the template in production workflows.

Best for

Extracting entities from articles or notes
Turning meeting notes into action items
Normalizing messy text before downstream automation

Expected output

Valid JSON only
Null for missing fields
No hallucinated facts
Stable schema matching

Variables to customize

schema

Target JSON schema or shape

Example: { customer, issue_type, due_date, action_items[] }

text

Source content to parse

Example: Meeting notes, email thread, article

Optimization tips

Put the schema directly in the prompt, not just in your head.
Tell the model how to handle missing values.
If output validity matters, validate it after generation and retry with the error message.

Example use case

Extract customer name, blocker, owner, due date, and actions from a long support escalation email.

Expected result

The model returns a clean JSON object that can be stored or processed by code without manual cleanup.