spaCy NER Skill

SkillAI & models

spaCy NER model training and entity extraction for conversational AI

Instructions available. Your AI can read the instructions. Execution depends on the setup they require.

Account requirements not reviewed. Check the skill instructions before use; ahel provides instructions and does not run this skill.

Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.

Then ask your AI: use the spaCy NER Skill skill

What this skill tells your AI

The instructions your AI receives, as published by a5c-ai/babysitter in library/specializations/ai-agents-conversational/skills/spacy-ner/SKILL.md and read by ahel’s review.

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

NER: Named Entity Recognition
EntityLinker: Link to knowledge bases
EntityRuler: Rule-based matching
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)

Signals

GitHub stars: 2k
Forks: 112
Last commit: Sep 2026

Advanced

Item type: skill
Key: spacy-ner
Source: github.com/a5c-ai/babysitter

github.com/a5c-ai/babysitter