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Define and enforce policies, access controls, and compliance rules over Semantica knowledge graphs.
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基于 SOC 职业分类
Semantica full-stack knowledge graph skill for context graphs, decision intelligence, explainability, extraction, reasoning, visualization, ontology, provenance, policy, and export workflows.
Analyze cause-and-effect relationships in the Semantica knowledge graph — causal chains, interventions, counterfactuals, and causal influence scores.
Explain Semantica reasoning, decision logic, and graph results with traceability, causal context, and human-readable rationale.
Detect duplicate entities, duplicate groups, and relationship duplicates in Semantica using fuzzy matching, schema heuristics, and graph similarity.
Export Semantica graphs, results, and provenance to JSON, RDF, Parquet, CSV, GraphML, and other formats.
Ingest data from files, databases, APIs, or streams into Semantica knowledge graphs with schema mapping and entity linking.
| name | policy |
| description | Define and enforce policies, access controls, and compliance rules over Semantica knowledge graphs. |
Apply policy rules and checks. Usage: /semantica:policy <task> [args]
$ARGUMENTS = task + optional policy name, rule set, or target entity.
check [--rule <name>] [--target <id>]Run policy checks against the graph.
from semantica.policy import PolicyEngine
engine = PolicyEngine()
result = engine.check(rule_name=rule_name, target=target)
Output: compliance status, failing rules, and remediation guidance.
listList available policy rules and categories.
rules = engine.list_rules()
Return: rule name, description, severity, and category.