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KaifAhmad1
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Add a Cite Us section to the README with BibTeX citation info, and align it with docs/citation.md (author/organization: Semantica, 2026). Update LICENSE and docs/project-license.md copyright holder to Semantica, and replace the stale Hawksight-AI GitHub org slug with semantica-agi across READMEs, plugin manifests, cookbook notebooks, and GitHub templates.
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13 KiB
Export Module - Comprehensive Guide
Overview
This notebook provides a comprehensive guide to Semantica's Export Module, which enables exporting knowledge graphs, entities, relationships, and data to multiple formats. The module supports 8 export formats (RDF, JSON, CSV, Graph, YAML, OWL, Vector, LPG) plus report generation capabilities.
Documentation: API Reference
Export Module Architecture
The Export Module consists of:
Core Exporter Classes (9 classes)
RDFExporter- RDF format export (Turtle, RDF/XML, JSON-LD, N-Triples, N3)JSONExporter- JSON and JSON-LD format exportCSVExporter- CSV format export for tabular dataGraphExporter- Graph format export (GraphML, GEXF, DOT)SemanticNetworkYAMLExporter- Semantic network YAML exportYAMLSchemaExporter- Schema YAML exportOWLExporter- OWL format export for ontologiesVectorExporter- Vector embedding export for vector storesLPGExporter- LPG format export for Neo4j, Memgraph, and similar databases
Supporting Classes (4 classes)
RDFSerializer- RDF serialization engine for format conversionRDFValidator- RDF validation engine for syntax checkingNamespaceManager- RDF namespace management and conflict resolutionReportGenerator- Report generation (HTML, Markdown, JSON, Text)
Registry & Configuration (2 classes + 2 instances)
MethodRegistry- Registry for custom export methodsmethod_registry- Global registry instanceExportConfig- Configuration manager for export moduleexport_config- Global configuration instance
Learning Objectives
By the end of this notebook, you will be able to:
- Export knowledge graphs to all supported formats (RDF, JSON, CSV, Graph, YAML, OWL, Vector, LPG)
- Use exporter classes directly for fine-grained control
- Generate professional reports in multiple formats
- Register and use custom export methods
- Configure export settings via environment variables or config files
- Use RDF serialization, validation, and namespace management
Installation
Install Semantica from PyPI:
pip install semantica
# Or with all optional dependencies:
pip install semantica[all]
Step 1: JSON Export
Export knowledge graph to JSON format using JSONExporter class.
JSONExporter Methods:
export()- Export any data to JSONexport_knowledge_graph()- Export knowledge graph to JSON/JSON-LDexport_entities()- Export entities to JSONexport_relationships()- Export relationships to JSON
In [ ]:
!pip install semanticaIn [ ]:
from semantica.export import JSONExporter
from semantica.kg import GraphBuilder
# Create exporter and builder
json_exporter = JSONExporter()
builder = GraphBuilder()
# Create sample knowledge graph
entities = [{"id": "e1", "type": "Organization", "name": "Apple Inc.", "properties": {}}]
relationships = []
kg = builder.build(entities + relationships)
# Export to JSON
json_exporter.export_knowledge_graph(kg, "output.json")
In [ ]:
from semantica.export import CSVExporter
# Create CSV exporter
csv_exporter = CSVExporter()
# Export entities to CSV
csv_exporter.export_entities(entities, "entities.csv")
In [ ]:
from semantica.export import RDFExporter
# Create RDF exporter
rdf_exporter = RDFExporter()
# Export to RDF format (Turtle by default)
rdf_exporter.export(kg, "output.ttl", format="turtle")In [ ]:
# TTL alias: format="ttl" is equivalent to format="turtle"
rdf_data = {
"entities": [
{"id": "e1", "text": "Apple Inc.", "type": "ORG", "confidence": 0.95},
{"id": "e2", "text": "Steve Jobs", "type": "PERSON", "confidence": 0.97},
],
"relationships": [
{"source_id": "e2", "target_id": "e1", "type": "founded_by", "confidence": 0.91},
],
}
rdf_exporter.export(rdf_data, "output.ttl", format="ttl")
result = rdf_exporter.validate_rdf(rdf_data)
print(f"Valid: {result['overall_valid']}")In [ ]:
from semantica.export import GraphExporter
# Create graph exporter
graph_exporter = GraphExporter()
# Export to GraphML format
graph_exporter.export_knowledge_graph(kg, "output.graphml", format="graphml")
In [ ]:
from semantica.export import OWLExporter
from semantica.ontology import OntologyGenerator
# Create OWL exporter and ontology generator
owl_exporter = OWLExporter()
generator = OntologyGenerator()
# Generate ontology from entities and relationships
# Note: Pass data as a dictionary to generate_ontology
ontology = generator.generate_ontology({
"entities": entities,
"relationships": relationships
})
# Export ontology to OWL
owl_exporter.export(ontology, "output.owl")