=GPT_EXTRACT() — pull structured values out of messy text

=GPT_EXTRACT() reads a text and returns just the values you ask for, comma-separated. Where REGEXEXTRACT() needs a pattern, =GPT_EXTRACT() understands meaning — “company names”, “the price”, “the person’s role” — which makes it the go-to cleanup formula in GPT for Sheets.

Syntax

=GPT_EXTRACT(text, to_extract)
Parameter Required Description
text yes The input text to extract from — usually a cell reference.
to_extract yes What to pull out, e.g. "email, country". Comma-separated values or a range.

Examples

Get emails out of scraped “Contact us” text in A2 (lead list building):

=GPT_EXTRACT(A2, "email")

Pull company names from a LinkedIn bio:

=GPT_EXTRACT("I worked at Apple for 5 years and at Amazon for 3 years.", "companies")

Extract several fields at once from an order confirmation email in A2:

=GPT_EXTRACT(A2, "order number, total amount, delivery date")

Mine product specs from an e-commerce description:

=GPT_EXTRACT(A2, "material, color, weight")

Tips

  • Multiple fields come back comma-separated — wrap the result with SPLIT(cell, ",") to break them into columns.
  • If a field is missing from the text, the model may say so in words; add “return N/A if not found” style instructions via =GPT() when you need strict output.
  • Drag the formula down to process a whole column — GPT for Sheets handles up to 10,000 results per hour.
  • Finished extracting? Use Replace all GPT formulas with results in the sidebar to freeze the values.

Try it

=GPT_EXTRACT() ships with GPT for Sheets — no API keys needed. Install the add-on from the Google Workspace Marketplace.