// Export VeritasReason graphs, results, and provenance to JSON, RDF, Parquet, CSV, GraphML, and other formats.
| name | export |
| description | Export VeritasReason graphs, results, and provenance to JSON, RDF, Parquet, CSV, GraphML, and other formats. |
Export knowledge graph data. Usage: /veritasreason:export <format> [args]
$ARGUMENTS = format + optional target or destination.
json [--output <path>] [--filter <query>]Export graph data as JSON.
from veritasreason.export.methods import export_json
export_json(data=graph_data, file_path=output, format='json')
Output: JSON file or inline JSON payload.
rdf [--format turtle|rdfxml|jsonld|ntriples|n3] [--output <path>]Export the graph in RDF serialization.
from veritasreason.export.methods import export_rdf
export_rdf(data=graph_data, file_path=output, format='turtle')
Return: RDF text or file path.
parquet [--output <path>]Export nodes and edges to Parquet for analytics.
from veritasreason.export.methods import export_parquet
export_parquet(data=graph_data, file_path=output, compression='snappy')
Output: Parquet dataset ready for downstream processing.
graphml|gexf|dot [--output <path>]Export the graph to a supported graph format.
from veritasreason.export import GraphExporter
exporter = GraphExporter(format='graphml', include_attributes=True)
exporter.export(graph_data, output)
Output: Graph format file suitable for visualization tools.
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.