Feature Extraction
Document Structure Extraction
Extract structured document layout with sections, relationships, and VLM-corrected OCR
Why do anything?
Complex documents have structure (sections, tables, figures) that flat text extraction loses.
Why now?
Document understanding requires preserving layout and relationships.
Why this feature?
Extract document graph with sections, relationships, and VLM correction for OCR errors. Generates 1024D embeddings.
How It Works
Document graph extractor preserves document structure with VLM-powered correction.
1
Layout Analysis
Detect sections, tables, figures
2
Graph Building
Build relationship graph between sections
3
VLM Correction
Vision-language model corrects OCR errors
4
Embedding
Generate 1024D embeddings per section
Why This Approach
Graph structure preserves document semantics. VLM correction improves text quality.
Where This Is Used
Integration
client.collections.create(feature_extractor={"feature_extractor_name": "document_graph_extractor", "version": "v1"})