/spacy-ner

name: spacy-ner
description: spaCy NER model training and entity extraction for conversational AI
allowed-tools:
  - Read
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graph:
  domains: [domain:software-engineering]
  specializations: [specialization:ai-agents-conversational]
  skillAreas: [skill-area:natural-language-processing, skill-area:feature-engineering]
  roles: [role:ml-engineer, role:backend-engineer]
  workflows: [workflow:ml-model-lifecycle, workflow:feature-development]

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)