goldenprofile-native
PyO3 binding for goldenprofile-core — the
Virtual Fingerprint / Semantic Signature engine.
Cross-document entity resolution over rigid, LLM-synthesized profiles
(name | category | anchor | attribute) for graph nodes and edges. Built to
repair the multi-hop knowledge-graph "shatter": disjoint neighborhoods reunite
into one entity (the defining attribute can only add confidence, never veto a
merge) while distinct entities stay apart (a hard name + category gate).
import json
from goldenprofile_native import resolve_json
req = {
"profiles": [
{"kind": "node", "name": "Thomas Nabbes", "category": "Playwright",
"anchor": "17th Century England", "attribute": "Wrote Play X"},
{"kind": "node", "name": "Nabbes", "category": "Playwright",
"anchor": "UNKNOWN", "attribute": "Born 1605"},
],
# "embeddings": [[...], [...]], # optional: one per profile, for semantic blocking
# "config": {"scoring": {"merge_threshold": 0.72}}, # optional partial override
}
res = json.loads(resolve_json(json.dumps(req)))
res["clusters"] # -> [[0, 1]] the two Nabbes mentions reunited
The compute is in the pyo3-free goldenprofile-core crate; this is a thin
JSON-boundary marshaling layer, so Python, WASM, and C surfaces produce
byte-identical clusters by construction. Part of the
goldengraph program.
1 maintainer
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