Stop getting paragraphs when all you need is a table.
AI models default to conversational output. Ask for “the price, date, and vendor” without specifying a format, and you’ll get a nicely worded sentence, a preamble, maybe a closing thought. Useful in some contexts. Annoying when you just need clean, structured data.
The original poster shared a dead-simple technique to fix this: Format Forcing.
The Prompt
Here it is, exactly as the author wrote it:
“Extract the following from [Text]: Date, Price, Vendor. Output as a Markdown Table. If data is missing, write N/A. Do not provide an intro or outro.”
That’s it. Copy it, swap in your target fields, and you’re done.
Why This Works
This prompt is short but it’s doing a lot of heavy lifting. Let’s break it down piece by piece:
- Explicit extraction targets (“Date, Price, Vendor”): No ambiguity about what to look for. The model isn’t guessing what’s important to you.
- Forced output format (“Output as a Markdown Table”): This is the core of the technique. By naming the exact format, you override the model’s default behavior of free-form prose.
- Null handling (“If data is missing, write N/A”): This prevents the model from skipping fields it can’t find or making up plausible-sounding values. N/A is explicit and honest.
- Output suppression (“Do not provide an intro or outro”): This is the secret weapon. Removing filler text makes the output paste-ready, pipeline-ready, human-scannable in seconds.
The combination of all four elements is what makes it work so cleanly. Any one of them alone is useful. All four together produce output that’s genuinely structured and reliable.
Use Cases
This pattern applies far beyond invoices and receipts:
- 📋 Extracting specs from product descriptions (model, dimensions, weight, price)
- 📰 Pulling key facts from news articles (who, what, when, where)
- 📄 Parsing contract clauses (party names, dates, obligations, penalties)
- 🛒 Scraping competitor pricing pages for comparison tables
- 📧 Organizing email threads into action-item logs
Anywhere you’re feeding unstructured text in and want clean rows out, this pattern applies.
Prompt of the Day
“Extract the following from [Text]: Date, Price, Vendor. Output as a Markdown Table. If data is missing, write N/A. Do not provide an intro or outro.”
Two Variations Worth Trying
Variation 1: JSON instead of Markdown
Swap “Output as a Markdown Table” for “Output as a JSON array of objects.” This is better if you’re feeding the result into code rather than a document.
Variation 2: Confidence flagging
Add one line: “If you are uncertain about a value, add a question mark after it.” This turns your N/A logic into a three-state system: found, missing, or uncertain. Much more useful when extraction accuracy matters.
Head over to the original thread on r/PromptEngineering to see if others have shared their own Format Forcing variations.
The ‘Data Extraction’ Schema.
by u/Significant-Strike40 in PromptEngineering