spacy-ner

# 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)