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Rudy CelekliandClaude Opus 5.5
7a32f3324e
_fold_confidence normalized the confidence/confidence_score pair on edges and hyperedges, but nodes passed through the build verbatim, so a model emitting a lowercase enum value, a bare float, or a drifted word for a node's confidence landed in graph.json as-is. Fold it in _fold_node_aliases, which both build_from_json and build_merge already call, so nodes share one normalization contract with edges. Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
225 lines
8.1 KiB
Python
225 lines
8.1 KiB
Python
"""LLM field aliases: node file/path/filepath -> source_file, edge relationship -> relation."""
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from __future__ import annotations
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import io
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from contextlib import redirect_stderr
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from graphify.build import (
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_fold_confidence,
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_fold_edge_aliases,
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_fold_node_aliases,
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build_from_json,
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)
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def test_edge_relationship_folds_to_relation():
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edge = {"source": "a", "target": "b", "relationship": "calls"}
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_fold_edge_aliases(edge)
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assert edge["relation"] == "calls"
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assert "relationship" not in edge
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def test_edge_relation_wins_over_relationship():
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edge = {"source": "a", "target": "b", "relation": "imports", "relationship": "calls"}
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_fold_edge_aliases(edge)
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assert edge["relation"] == "imports"
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def test_node_file_folds_to_source_file():
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node = {"id": "a", "label": "A", "file": "foo.ts"}
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_fold_node_aliases(node)
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assert node["source_file"] == "foo.ts"
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assert "file" not in node
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def test_node_path_folds_to_source_file():
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node = {"id": "a", "label": "A", "path": "bar.py"}
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_fold_node_aliases(node)
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assert node["source_file"] == "bar.py"
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assert "path" not in node
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def test_node_filepath_folds_to_source_file():
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node = {"id": "a", "label": "A", "filepath": "baz.go"}
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_fold_node_aliases(node)
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assert node["source_file"] == "baz.go"
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def test_node_source_file_wins_over_alias():
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node = {"id": "a", "label": "A", "source_file": "real.py", "file": "other.py"}
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_fold_node_aliases(node)
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assert node["source_file"] == "real.py"
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def test_numeric_confidence_folds_to_inferred_and_backfills_score():
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edge = {"source": "a", "target": "b", "confidence": 0.85}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == "INFERRED"
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assert edge["confidence_score"] == 0.85
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def test_numeric_confidence_does_not_override_an_existing_score():
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edge = {"source": "a", "target": "b", "confidence": 0.85, "confidence_score": 0.5}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == "INFERRED"
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assert edge["confidence_score"] == 0.5
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def test_model_drifted_string_confidence_folds_to_inferred():
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# "high"/"confirmed"/"medium-high"/"medium-low" are model drift from the
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# LLM semantic pass, not the documented EXTRACTED/INFERRED/AMBIGUOUS enum
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# (#4495): none of them parse as a float, so confidence_score is left
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# alone and only the enum field itself is repaired.
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for drifted in ("high", "confirmed", "medium-high", "medium-low"):
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edge = {"source": "a", "target": "b", "confidence": drifted}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == "INFERRED", drifted
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assert "confidence_score" not in edge, drifted
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def test_numeric_looking_string_confidence_backfills_score():
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"""A string that DOES parse as a float still backfills confidence_score,
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the same as a genuinely numeric confidence (#4495)."""
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edge = {"source": "a", "target": "b", "confidence": "0.85"}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == "INFERRED"
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assert edge["confidence_score"] == 0.85
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def test_lowercase_confidence_is_case_corrected_not_treated_as_drift():
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"""A case variant of a real enum value (#4495) IS the enum value, just
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mis-cased -- it must be corrected to its exact spelling, not treated as
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an unknown word that backfills confidence_score from a failed float
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parse of a string that was never meant to be a number."""
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edge = {"source": "a", "target": "b", "confidence": "inferred"}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == "INFERRED"
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assert "confidence_score" not in edge
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def test_valid_enum_confidences_are_left_untouched():
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for valid in ("EXTRACTED", "INFERRED", "AMBIGUOUS"):
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edge = {"source": "a", "target": "b", "confidence": valid}
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_fold_edge_aliases(edge)
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assert edge["confidence"] == valid
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assert "confidence_score" not in edge
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def test_hyperedge_confidence_folds_the_same_way():
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"""#4495: a hyperedge carries the same confidence/confidence_score pair
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an edge does, and had no fold of its own."""
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he = {"id": "h1", "nodes": ["a", "b"], "confidence": "high"}
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_fold_confidence(he)
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assert he["confidence"] == "INFERRED"
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he_numeric = {"id": "h2", "nodes": ["a", "b"], "confidence": 0.75}
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_fold_confidence(he_numeric)
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assert he_numeric["confidence"] == "INFERRED"
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assert he_numeric["confidence_score"] == 0.75
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def test_build_from_json_normalizes_drifted_confidence_without_warning():
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"""#4495 end to end: a graph carrying the exact warning text from the
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issue must build silently, with the edge and hyperedge confidence both
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repaired to the enum."""
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extraction = {
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"nodes": [
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{"id": "a", "label": "A", "file_type": "document", "source_file": "a.md"},
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{"id": "b", "label": "B", "file_type": "document", "source_file": "b.md"},
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],
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"edges": [
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{
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"source": "a", "target": "b", "relation": "references",
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"confidence": "confirmed", "source_file": "a.md",
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}
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],
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"hyperedges": [
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{"id": "h1", "nodes": ["a", "b"], "relation": "form", "confidence": "high"}
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],
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}
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err = io.StringIO()
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with redirect_stderr(err):
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G = build_from_json(extraction)
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assert "invalid confidence" not in err.getvalue()
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_, _, data = next(iter(G.edges(data=True)))
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assert data["confidence"] == "INFERRED"
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assert G.graph["hyperedges"][0]["confidence"] == "INFERRED"
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def test_build_from_json_normalizes_without_validation_warnings():
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extraction = {
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"nodes": [
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{"id": "a", "label": "A", "file_type": "code", "file": "foo.ts"},
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{"id": "b", "label": "B", "file_type": "code", "path": "bar.py"},
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],
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"edges": [
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{
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"source": "a",
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"target": "b",
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"relationship": "calls",
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"confidence": "EXTRACTED",
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"source_file": "foo.ts",
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}
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],
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}
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err = io.StringIO()
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with redirect_stderr(err):
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G = build_from_json(extraction)
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out = err.getvalue()
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assert "missing required field" not in out
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assert G.nodes["a"]["source_file"] == "foo.ts"
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assert G.nodes["b"]["source_file"] == "bar.py"
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assert G.number_of_edges() == 1
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_, _, data = next(iter(G.edges(data=True)))
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assert data["relation"] == "calls"
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def test_node_confidence_folds_the_same_way():
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"""#4529: a node carrying a confidence/confidence_score pair gets the same
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fold edges and hyperedges already have, instead of passing through the
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build verbatim."""
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drifted = {"id": "a", "label": "A", "confidence": "high"}
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_fold_node_aliases(drifted)
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assert drifted["confidence"] == "INFERRED"
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assert "confidence_score" not in drifted
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mis_cased = {"id": "b", "label": "B", "confidence": "extracted"}
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_fold_node_aliases(mis_cased)
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assert mis_cased["confidence"] == "EXTRACTED"
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assert "confidence_score" not in mis_cased
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numeric = {"id": "c", "label": "C", "confidence": 0.9}
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_fold_node_aliases(numeric)
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assert numeric["confidence"] == "INFERRED"
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assert numeric["confidence_score"] == 0.9
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def test_node_without_confidence_is_left_untouched():
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"""No behavior change for graphs whose nodes carry no confidence (#4529)."""
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node = {"id": "a", "label": "A", "source_file": "a.py"}
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_fold_node_aliases(node)
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assert "confidence" not in node
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assert "confidence_score" not in node
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def test_build_from_json_normalizes_node_confidence():
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"""#4529 end to end: a drifted node confidence reaches the built graph
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folded onto the enum, the same as an edge's."""
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extraction = {
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"nodes": [
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{
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"id": "a", "label": "A", "file_type": "document",
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"source_file": "a.md", "confidence": "extracted",
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},
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{
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"id": "b", "label": "B", "file_type": "document",
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"source_file": "b.md", "confidence": 0.7,
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},
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],
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"edges": [],
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}
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G = build_from_json(extraction)
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assert G.nodes["a"]["confidence"] == "EXTRACTED"
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assert G.nodes["b"]["confidence"] == "INFERRED"
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assert G.nodes["b"]["confidence_score"] == 0.7
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