Learning More¶

Additional resources, tutorials, and advanced learning materials for Semantica.

Structured Learning Paths¶

Beginner Path (1-2 hours)¶

1. Installation & Setup (15 min)

   • Installation Guide
   • Welcome to Semantica Cookbook: Comprehensive introduction
   • Topics: Framework overview, all modules, architecture, configuration
   • Difficulty: Beginner
   • Time: 30-45 minutes
   • Use Cases: First-time users, understanding the framework

2. Core Concepts (30 min)

   • Core Concepts
   • Getting Started Guide
   • Data Ingestion Cookbook: Learn to ingest from multiple sources
   • Topics: File, web, feed, stream, database ingestion
   • Difficulty: Beginner
   • Time: 15-20 minutes
   • Use Cases: Loading data from various sources

3. First Knowledge Graph (30 min)

   • Quickstart Tutorial
   • Your First Knowledge Graph Cookbook: Build your first knowledge graph
   • Topics: Entity extraction, relationship extraction, graph construction, visualization
   • Difficulty: Beginner
   • Time: 20-30 minutes
   • Use Cases: Learning the basics, quick start

4. Basic Operations (30 min)

   • Examples
   • Entity Extraction Cookbook: Learn entity extraction
   • Topics: Named entity recognition, entity types, extraction methods
   • Difficulty: Beginner
   • Time: 15-20 minutes
   • Use Cases: Understanding entity extraction

Intermediate Path (4-6 hours)¶

1. Advanced Concepts (1 hour)

   • Modules Guide
   • Building Knowledge Graphs Cookbook: Advanced graph construction
   • Topics: Graph building, entity merging, conflict resolution, temporal graphs
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Production graph construction
   • Embeddings Cookbook: Learn embeddings
   • Topics: Embedding generation, similarity search, vector operations
   • Difficulty: Beginner
   • Time: 20-30 minutes
   • Use Cases: Understanding embeddings, semantic search

2. Use Cases (1 hour)

   • Use Cases Guide
   • GraphRAG Complete Cookbook: Build production GraphRAG
   • Topics: GraphRAG, hybrid retrieval, graph traversal, LLM integration
   • Difficulty: Advanced
   • Time: 1-2 hours
   • Use Cases: Production GraphRAG systems

3. Advanced Examples (1 hour)

   • Examples
   • Advanced Extraction Cookbook: Advanced extraction patterns
   • Topics: Custom entity types, domain-specific extraction, hybrid methods
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Domain-specific extraction

4. Quality & Optimization (1 hour)

   • Quality Assurance
   • Performance Optimization
   • Multi-Source Data Integration Cookbook: Integrate multiple sources
   • Topics: Multi-source integration, entity resolution, conflict handling
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Building unified knowledge graphs

Advanced Path (8+ hours)¶

1. Advanced Architecture (2 hours)

   • Architecture Guide
   • Temporal Graphs Cookbook: Build temporal graphs
   • Topics: Time-stamped entities, temporal relationships, historical queries
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Time-aware knowledge graphs
   • Ontology Cookbook: Generate ontologies
   • Topics: Ontology generation, OWL, schema design
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Formal knowledge representation

2. Production Deployment (2 hours)

   • Security Best Practices
   • GraphRAG Complete Cookbook: Production GraphRAG
   • Topics: Production deployment, scalability, optimization
   • Difficulty: Advanced
   • Time: 1-2 hours
   • Use Cases: Production systems

3. Customization (2 hours)

   • Complete Visualization Suite Cookbook: Advanced visualization
   • Topics: Custom layouts, filtering, styling, multiple graph types
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Production visualizations
   • Multi-Format Export Cookbook: Advanced export patterns
   • Topics: Batch export, custom formats, format conversion
   • Difficulty: Intermediate
   • Time: 30-45 minutes
   • Use Cases: Production exports

Quick Reference¶

Common Operations¶

The typical workflow involves these steps:

1. Ingest documents using `FileIngestor`
2. Parse documents using `DocumentParser`
3. Extract entities and relationships using `NERExtractor` and `RelationExtractor`
4. Build knowledge graph using `GraphBuilder`
5. Generate embeddings using `TextEmbedder`

For complete examples, see: - Your First Knowledge Graph Cookbook: Complete workflow example - Welcome to Semantica Cookbook: All modules overview

Configuration Reference¶

Troubleshooting Guide¶

Performance Optimization¶

1. Batch Processing¶

Process multiple documents together for better throughput. Use batch processing when working with large document collections.

For examples, see: - Data Ingestion Cookbook: Batch ingestion patterns - Multi-Source Data Integration Cookbook: Advanced integration

2. Parallel Execution¶

Use parallel processing for independent operations to improve performance on multi-core systems.

3. Backend Selection¶

Security Best Practices¶

API Key Management¶

• DO: Use environment variables, rotate keys regularly.
• DON'T: Hardcode keys, commit to version control.

Data Privacy¶

• DO: Encrypt sensitive data, use local models.
• DON'T: Send PII to external APIs without protection.

FAQ¶

Q: What is Semantica? A: A framework for building knowledge graphs and semantic applications.

Q: Is Semantica free? A: Yes, it is open source. Some features (e.g., OpenAI) require paid APIs.

Q: Can I use Semantica in production? A: Yes, it is designed for production with proper configuration.

Next Steps¶

Continue your learning journey:

• Cookbook - Interactive Jupyter notebook tutorials
• API Reference - Complete API documentation
• Use Cases - Real-world applications
• Examples - Code examples and patterns

🍳 Recommended Next Cookbooks¶

• GraphRAG Complete: Production GraphRAG system
• Topics: GraphRAG, hybrid retrieval, LLM integration
• Difficulty: Advanced
• Time: 1-2 hours

• Use Cases: Production RAG applications

• RAG vs. GraphRAG Comparison: Understand the differences

• Topics: RAG comparison, reasoning gap, inference engines
• Difficulty: Intermediate
• Time: 45-60 minutes
• Use Cases: Choosing the right approach