Document Transformation
Document transformation is the process of converting unstructured documents into structured graph data based on your ontology. This is a core capability of Graphora that allows you to extract meaningful entities and relationships from your documents.The Transformation Process
When you submit documents to Graphora for transformation, the following steps occur:1
Document Upload
Documents are uploaded to the Graphora platform and validated.
2
Parsing
Documents are parsed into a format that can be processed by the extraction pipeline.
3
Entity Extraction
Entities defined in your ontology are identified and extracted from the documents.
4
Relationship Extraction
Relationships between entities are identified based on the ontology definitions.
5
Validation
Extracted entities and relationships are validated against the ontology constraints.
6
Graph Construction
A graph is constructed from the validated entities and relationships.
Supported Document Types
Graphora supports a variety of document types for transformation:- Text files (
.txt) - PDF documents (
.pdf) - PPT documents (
.ppt) - PPTX documents (
.pptx) - Word documents (
.doc) - Word documents (
.docx) - CSV files (
.csv) - JSON files (
.json) - YAML files (
.yaml) - XML files (
.xml)
Transformation in the Client Library
The Graphora client library provides methods for transforming documents and monitoring the transformation process:Transforming Documents
Checking Transformation Status
Retrieving the Transformed Graph
Transformation Stages
The transformation process goes through several stages, which you can monitor through thestage_progress field in the transformation status:
Handling Transformation Errors
If a transformation fails, you can check theerror field in the transformation status:
Best Practices for Document Transformation
To get the best results from document transformation:- Ensure your ontology is well-defined: The quality of extraction depends on your ontology
- Use appropriate document types: Different document types may yield different results
- Monitor transformation progress: Long documents may take time to process
- Handle errors gracefully: Check for and handle transformation errors
- Clean up after completion: Use
cleanup_transformto remove temporary files
Example: Complete Transformation Workflow
Here’s a complete example of transforming documents and handling the results:Next Steps
- Learn about Merging extracted data
- Explore the Graph data model
- Check out the API Reference for detailed information
