gnn-ontology

name	gnn-ontology
description	GNN Active Inference ontology processing and validation. Use when working with ActInfOntologyAnnotation sections, mapping GNN variables to ontology terms, validating semantic annotations, or exploring Active Inference concept hierarchies.

GNN Ontology Processing (Step 10)

Purpose

Processes Active Inference ontology annotations in GNN models. Maps GNN variables to standardized Active Inference concepts and validates semantic consistency.

Key Commands

# Run ontology processing
python src/10_ontology.py --target-dir input/gnn_files --output-dir output --verbose

# As part of pipeline
python src/main.py --only-steps 10 --verbose

Ontology Term Mapping

GNN Annotation	Ontology Concept	Description
LikelihoodMatrix	A matrix	Observation model
TransitionMatrix	B matrix	State dynamics
HiddenState	s vector	Latent state beliefs
Observation	o vector	Sensory observations
Policy	π	Action sequences
Preference	C matrix	Preferred observations

API

from ontology import (
    process_ontology, parse_gnn_ontology_section, process_gnn_ontology,
    load_defined_ontology_terms, validate_annotations,
    generate_ontology_report_for_file, parse_annotation,
    OntologyProcessor, OntologyValidator
)

# Process ontology section from GNN content
parsed = parse_gnn_ontology_section(gnn_content)

# Load defined ontology terms
terms = load_defined_ontology_terms()

# Validate annotations against defined terms
result = validate_annotations(annotations_list, terms)

# Use OntologyProcessor class
processor = OntologyProcessor()
result = processor.process_ontology(data)

# Use OntologyValidator class
validator = OntologyValidator()
is_valid = validator.validate_ontology(content)

Key Exports

• process_ontology — main pipeline processing function
• parse_gnn_ontology_section — extract ontology from GNN content
• validate_annotations — validate against known terms
• OntologyProcessor — class with process_ontology(), validate_terms()
• OntologyValidator — class with validate_ontology(), check_consistency()

Output

• Ontology mappings in output/10_ontology_output/
• Validation reports for annotation consistency

MCP Tools

This module registers tools with the GNN MCP server (see mcp.py):

• extract_ontology_annotations
• list_standard_ontology_terms
• process_ontology
• validate_ontology_terms

References

• AGENTS.md — Module documentation
• README.md — Usage guide
• SPEC.md — Module specification

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Documentation

• README: Module Overview
• AGENTS: Agentic Workflows
• SPEC: Architectural Specification
• SKILL: Capability API