spaCy NER Skill

Capabilities

• Train custom spaCy NER models
• Configure entity extraction pipelines
• Design annotation schemas
• Implement entity linking
• Set up model evaluation
• Deploy efficient NER inference

Target Processes

• entity-extraction-slot-filling
• chatbot-design-implementation

Implementation Details

spaCy Components

1. NER: Named Entity Recognition
2. EntityLinker: Link to knowledge bases
3. EntityRuler: Rule-based matching
4. SpanCategorizer: Overlapping entities

Training Configuration

• config.cfg setup
• Training data format (spaCy v3)
• Augmentation strategies
• Evaluation metrics

Configuration Options

• Base model selection (en_core_web_*)
• Custom entity types
• Training parameters
• GPU acceleration
• Model packaging

Best Practices

• Quality annotation data
• Balance entity types
• Use prodigy for annotation
• Regular model evaluation

Dependencies

• spacy
• spacy-transformers (optional)