Extract Structured Data

Action ID: openai_extract_structured_data

Description

Returns structured data from provided unstructured text. This node uses OpenAI's Structured Outputs capability to reliably extract and validate data according to a JSON Schema you define, ensuring the model always returns properly formatted results.

Provider

OpenAI

Connection

Name	Description	Required	Category
OpenAI Connection	The OpenAI connection to use for extracting structured data.	✓	openai

Input Parameters

Name	Type	Required	Default	Description
model	dropdown	-	gpt-4o-2024-08-06	The model to use for extracting structured data. Use gpt-4o-2024-08-06 or later for best results.
text	string	✓	-	The text from which to extract structured data.
schema_name	string	-	extracted_data	A name for the schema (required by OpenAI).
json_schema	object	✓	-	The JSON Schema that defines the structure of the data to extract. Must be a valid JSON Schema object with type='object', properties defined, and additionalProperties=false.
strict	boolean	-	true	Whether to enforce strict schema validation. When true, the model will always generate responses that adhere to the supplied schema.
system_prompt	string	-	-	Optional system prompt to guide the extraction process.

View JSON Schema

{
  "description": "Extract Structured Data node input.",
  "properties": {
    "model": {
      "default": "gpt-4o-2024-08-06",
      "description": "The model to use for extracting structured data. Use gpt-4o-2024-08-06 or later for best results.",
      "title": "Model",
      "type": "string"
    },
    "text": {
      "description": "The text from which to extract structured data.",
      "title": "Unstructured Text",
      "type": "string"
    },
    "schema_name": {
      "default": "extracted_data",
      "description": "A name for the schema (required by OpenAI).",
      "title": "Schema Name",
      "type": "string"
    },
    "json_schema": {
      "description": "The JSON Schema that defines the structure of the data to extract. Must be a valid JSON Schema object with type='object', properties defined, and additionalProperties=false.",
      "title": "JSON Schema",
      "type": "object"
    },
    "strict": {
      "default": true,
      "description": "Whether to enforce strict schema validation. When true, the model will always generate responses that adhere to the supplied schema.",
      "title": "Strict Mode",
      "type": "boolean"
    },
    "system_prompt": {
      "description": "Optional system prompt to guide the extraction process.",
      "title": "System Prompt",
      "type": "string"
    }
  },
  "required": [
    "text",
    "json_schema"
  ],
  "title": "ExtractStructuredDataInput",
  "type": "object"
}

Output Parameters

Name	Type	Description
data	object	The extracted structured data matching the provided schema.

View JSON Schema

{
  "description": "Response from extracting structured data.",
  "properties": {
    "data": {
      "description": "The extracted structured data.",
      "title": "Data",
      "type": "object"
    }
  },
  "title": "ExtractStructuredDataResponse",
  "type": "object"
}

How It Works

This node leverages OpenAI's Structured Outputs feature to reliably extract data from unstructured text. You provide a JSON Schema that describes the structure you want to extract, and the model uses this schema to guide its response. In strict mode (default), the model is constrained to always return valid JSON that conforms to your schema, eliminating the need for complex parsing or validation logic. The extracted data is returned directly as a JSON object.

Usage Examples

Example 1: Extract Contact Information

Input:

text: "John Smith, Software Engineer, works at Acme Corp. His email is [email protected] and phone is 555-1234."
schema_name: "contact_info"
json_schema: {
  "type": "object",
  "properties": {
    "name": {"type": "string"},
    "title": {"type": "string"},
    "company": {"type": "string"},
    "email": {"type": "string"},
    "phone": {"type": "string"}
  },
  "required": ["name", "email"],
  "additionalProperties": false
}
strict: true

Output:

data: {
  "name": "John Smith",
  "title": "Software Engineer",
  "company": "Acme Corp",
  "email": "[email protected]",
  "phone": "555-1234"
}

Example 2: Extract Product Information

Input:

text: "The TechWidget 3000 is a revolutionary device that costs $299.99 and comes in silver, blue, and black colors. It has a 2-year warranty and is rated 4.5 stars."
schema_name: "product"
json_schema: {
  "type": "object",
  "properties": {
    "product_name": {"type": "string"},
    "price": {"type": "number"},
    "colors": {"type": "array", "items": {"type": "string"}},
    "warranty_years": {"type": "integer"},
    "rating": {"type": "number"}
  },
  "required": ["product_name", "price"],
  "additionalProperties": false
}
strict: true

Output:

data: {
  "product_name": "TechWidget 3000",
  "price": 299.99,
  "colors": ["silver", "blue", "black"],
  "warranty_years": 2,
  "rating": 4.5
}

Common Use Cases

• Data Extraction: Extract structured information from unstructured documents

• Form Filling: Automatically populate form fields from text descriptions

• Information Parsing: Parse complex text into organized data structures

• Document Processing: Extract key information from PDFs, emails, or documents

• API Data Preparation: Convert text into JSON for downstream APIs

• Data Classification: Categorize and structure unstructured information

• Entity Recognition: Extract and organize entities with relationships

Error Handling

Error Type	Cause	Solution
Invalid Schema	Schema missing required fields or incorrectly formatted	Ensure schema has type='object', properties defined, and additionalProperties=false
Schema Validation Failed	Model cannot strictly adhere to schema	Simplify schema, use more flexible field types, or disable strict mode
Model Not Found	Selected model doesn't exist or access not granted	Verify model availability and ensure API key has access
Extraction Failed	Model cannot extract data from provided text	Provide clearer text with more explicit information
Authentication Error	Invalid or missing OpenAI API key	Verify your OpenAI connection is properly configured
Token Limit Exceeded	Text is too long for model's context window	Reduce text length or use a model with larger context

Notes

• Schema Requirements: Schemas must have type='object', define properties, and set additionalProperties=false for validation to work correctly.

• Strict Mode: Highly recommended for reliable extraction. When enabled, responses are guaranteed to conform to your schema.

• Model Selection: Use gpt-4o-2024-08-06 or later for best results with Structured Outputs.

• System Prompts: Use system prompts to guide extraction behavior, such as "Extract only explicitly stated information" or "Infer implied values where reasonable."

• Nested Objects: You can define nested properties for complex hierarchical data structures.

• Array Handling: Use array types for extracting lists of items with consistent structure.