spaCy NER model training and entity extraction for conversational AI
apm install @a5c-ai/spacy-ner[](https://apm-p1ls2dz87-atlamors-projects.vercel.app/packages/@a5c-ai/spacy-ner)---
name: spacy-ner
description: spaCy NER model training and entity extraction for conversational AI
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---
# 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)