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LangExtract tutorial: extract entities from text with exact sources

Define a prompt and one good example, then extract entities tied to their exact text spans.

Credentials. Cloud model extraction uses your API key and bills per call.

Who it is forAn analyst turning hundreds of free-text notes into a structured table.

The problemLLM extraction without grounding is hard to verify.

The outcomeExtractions that each point to the exact source text.

What you need first

  • Python
  • An API key for a cloud model, or a supported local or custom provider

Steps

  1. Install the LangExtract package
  2. Write a prompt describing what to extract
  3. Provide an ExampleData with Extraction entries
  4. Run extraction on your text and review the grounded results

Prompt for your agent

Using google/langextract, extract <entity types> from <document> with one example, and list each extraction with its source span. Verify three spans against the original text.

Caveat. Extraction quality depends heavily on the example you provide.

Use this in your AI agent

Ask your agent

Using the Deduped MCP, get the setup steps for google/langextract and "Extract structured entities from text with exact sources"

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claude mcp add --transport http deduped https://dedupedai.com/mcp

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