VeritasGraph

VeritasReason 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 VeritasReason knowledge graph — causal chains, interventions, counterfactuals, and causal influence scores.

Track and inspect graph changes, diffs, temporal updates, and the impact of new data on VeritasReason knowledge graphs.

Full decision lifecycle in VeritasReason � record, query, find precedents (hybrid/advanced), analyze influence, explain, insights dashboard, list, and record exceptions. Uses AgentContext, ContextGraph, DecisionQuery, CausalChainAnalyzer, DecisionRecorder.

Detect duplicate entities, duplicate groups, and relationship duplicates in VeritasReason using fuzzy matching, schema heuristics, and graph similarity.

Generate, inspect, and use node/text embeddings in VeritasReason — compute Node2Vec embeddings, find similar nodes, score link predictions, batch similarity, and pairwise similarity. Uses NodeEmbedder, SimilarityCalculator, LinkPredictor, and AgentContext. Sub-commands: compute, similar, similarity, predict-link, top-links, batch, pairwise.

Explain VeritasReason reasoning, decision logic, and graph results with traceability, causal context, and human-readable rationale.

Export VeritasReason graphs, results, and provenance to JSON, RDF, Parquet, CSV, GraphML, and other formats.

Run the full VeritasReason semantic extraction pipeline on a file or selected text — NER, relations, events, coreference resolution, triplets, and validation. Clears result cache before each run. Returns Markdown tables with entity/relation/event/triplet results and inline validator warnings.

Ingest data from files, databases, APIs, or streams into VeritasReason knowledge graphs with schema mapping and entity linking.

Manage ontology schemas, concepts, relationships, and alignments for VeritasReason knowledge graphs.

Define and enforce policies, access controls, and compliance rules over VeritasReason knowledge graphs.

Trace data lineage, source attribution, audit trails, and provenance assertions in VeritasReason graphs.

Query the VeritasReason knowledge graph using SPARQL, Cypher, keyword search, and structured graph query patterns.

Run reasoning over the VeritasReason knowledge graph — deductive logic, abductive hypothesis generation, Datalog programs, SPARQL queries, Rete network evaluation. Uses DeductiveReasoner, AbductiveReasoner, DatalogReasoner, SPARQLReasoner, ReteEngine. Sub-commands: deductive, abductive, datalog, sparql, rete, prove, hypotheses.

Temporal graph operations on VeritasReason — scoped queries at a point in time, graph snapshots, node change timelines, temporal causal analysis, and graph state reconstruction. Uses AgentContext.find_precedents(as_of=), ContextGraph.state_at(), CausalChainAnalyzer.trace_at_time(), and TemporalQueryRewriter. Sub-commands: query, snapshot, timeline, causal-at, precedents-at.

Validate VeritasReason pipelines, extraction quality, graph schemas, and ontology consistency. Returns structured error/warning checklists. Uses PipelineValidator, PipelineBuilder.validate_pipeline(), GraphValidator, and OntologyValidator. Sub-commands: pipeline, step, dependencies, extraction, graph, ontology, performance.

Visualize the VeritasReason knowledge graph — topology, centrality, communities, paths, embeddings, decision insights, and temporal evolution. Uses GraphAnalyzer, CentralityCalculator, CommunityDetector, PathFinder, and ContextGraph analytics. Sub-commands: topology, centrality, community, path, decision-graph, insights, temporal, embedding.