Extract (New)
Extract structured data from text using AWS Bedrock
Node Overview
| Property | Details |
|---|---|
| Purpose | Extract structured information from unstructured text |
| Usage | Transform free-form text into structured data formats |
| Category | Intelligent Assist |
| Type | AI Object |
| Security | Safe data extraction with validation |
Key Capabilities
- Text Extraction- Extract structured data from text content
- Dynamic Outputs- Configure custom extraction fields
- AI Processing- Leverage advanced language models
- Structured Results- Return data in organized formats
- Flexible Parsing- Handle various text formats and structures
Node Inputs
Required Parameters
| Parameter | Type | Description |
|---|---|---|
| Extract From | textarea |
The text content to extract data from |
| Model | modelSettings |
AI model for text analysis and extraction |
| Data | object |
Input data context and additional variables |
Optional Parameters
| Parameter | Type | Default | Description |
|---|---|---|---|
| Outputs | dynamicOutput2 |
- | Custom output fields to extract |
| Model Config | object |
- | Additional model configuration options |
Node Output
Response Object
{
extractedData: {
[fieldName: string]: any // Dynamic fields based on configured outputs
}
}
Returns structured data extracted from the input text
Node Functionality
The Extract node provides intelligent data extraction:
Text Processing
- Content Analysis- Understand and parse text content
- Entity Recognition- Identify and extract specific entities
- Structure Inference- Determine data relationships and structure
Data Extraction
- Custom Fields- Define specific data fields to extract
- Type Handling- Extract various data types (strings, numbers, dates)
- Validation- Ensure extracted data meets expected formats
Key Features
Core Configuration
| Feature | Description |
|---|---|
| Text Input | Process various types of unstructured text |
| Dynamic Outputs | Configure custom extraction fields and data types |
| Model Selection | Choose appropriate models for different extraction tasks |
Advanced Extraction
AI-Powered Data Mining
- Entity Extraction- Identify and extract specific data entities
- Structure Recognition- Understand text structure and relationships
- Format Conversion- Transform unstructured data to structured formats
When to Use
Choose the Extract node when you need to:
Data Processing
- Information Extraction- Pull specific data from documents
- Document Parsing- Extract data from forms and reports
- Email Processing- Extract information from email content
Enterprise Applications
- Form Processing- Extract data from submitted forms
- Invoice Processing- Extract billing information from invoices
- Contact Extraction- Pull contact information from text
Integration Scenarios
- News Processing- Extract key information from news articles
- Social Media Analysis- Extract insights from social posts
- Report Analysis- Extract metrics and data from reports
Important Considerations
Configuration Requirements
| Aspect | Requirement | Impact |
|---|---|---|
| Text Quality | Clear, structured text content | Affects extraction accuracy and completeness |
| Output Definition | Well-defined extraction fields | Determines what data is captured |
| Model Selection | Text-capable models | Required for natural language processing |
Performance Factors
| Factor | Description | Optimization |
|---|---|---|
| Text Length | Amount of text to process | Balance detail with processing efficiency |
| Field Count | Number of fields to extract | More fields increase processing time |
| Processing Time | Model inference time | Choose appropriate models for speed vs accuracy |
Security & Safety
| Security Feature | Protection | Benefit |
|---|---|---|
| Input Validation | Validate text inputs | Prevent malicious content processing |
| Output Sanitization | Clean extracted data | Ensure safe data consumption |
| Data Validation | Validate extracted fields | Prevent incorrect data extraction |
Best Practices
Development Guidelines
- Field Definition- Clearly define what data to extract
- Text Preparation- Pre-process text for optimal extraction
- Testing- Test with various text formats and structures
- Validation Rules- Define validation rules for extracted data
Optimization Strategies
- Model Selection- Choose models based on data type and speed needs
- Field Optimization- Limit fields to essential data points
- Cost Monitoring- Track usage for budget optimization
- Preprocessing- Clean and structure text before extraction
Example Use Cases
Invoice Data Extraction
Purpose: Extract billing information from invoices
Text: Invoice document content
Outputs: Vendor, Amount, Date, Invoice Number, Line Items
Result: Structured invoice data for processing
Contact Information Extraction
Purpose: Extract contact details from business cards or emails
Text: Business card scan or email signature
Outputs: Name, Email, Phone, Company, Address
Result: Structured contact information
Report Metrics Extraction
Purpose: Extract key metrics from business reports
Text: Quarterly report content
Outputs: Revenue, Growth, Market Share, KPIs
Result: Structured business metrics
News Article Information Extraction
Purpose: Extract key information from news articles
Text: News article content
Outputs: Headline, Date, Author, Summary, Keywords
Result: Structured article metadata