spacy-ner

Included with Lifetime

$97 forever

spaCy NER model training and entity extraction for conversational AI

General

What this skill does


# 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)

Files: 2

Size: 1.6 KB

Complexity: 10/100

Category: General

Source: https://github.com/a5c-ai/babysitter/tree/main/library/specializations/ai-agents-conversational/skills/spacy-ner

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