Review feedback: analyze_decision_influence(), trace_decision_causality(),
and find_precedents() had the same vocabulary split as get_causal_chain().
The first two read edge_type_index, which is keyed by the RAW edge_type
string, so they now filter index keys by normalized type; find_precedents()
accepts the analyzer's 'precedes' spelling alongside PRECEDENT_FOR.
Adds regression tests for all three call sites.
* docs(shacl): warn that rdfs:range makes sh:class unfalsifiable under entailment (#1130)
* docs(shacl): self-contained pitfall example, sh:node coverage, and wrapper clarifications (#1130)
Review feedback: normalization must not turn invalid inputs into
AttributeError. Non-string relationship types now raise ValueError before
normalization, matching the pre-change behavior; strings are stripped
before alias lookup.
get_causal_chain() matched only the canonical uppercase spellings
(CAUSED, INFLUENCED, PRECEDENT_FOR), while CausalChainAnalyzer's
vocabulary includes the present-tense forms (causes, influences,
leads_to, supports) — and the two differ in word form, not just case,
so case-insensitive matching alone would still miss them. An edge
recorded as "causes" produced an empty audit chain.
Storage normalizes both vocabularies onto the canonical types via
_CAUSAL_EDGE_ALIASES; traversal accepts the union (_CAUSAL_TRAVERSAL_TYPES).
add_causal_relationship() now accepts either spelling and stores the
canonical form.
CodeQL (py/incomplete-url-substring-sanitization) flagged the "https://schema.org/"
in flattened check because it pattern-matches on URL-ish strings tested with `in`.
flattened is always a list here, so the check was already exact membership, not a
substring test on untrusted input, but the ambiguous idiom tripped the scanner.
Rewrite as an explicit equality comparison so the intent is unambiguous.
analyze_evolution() previously appended a constant placeholder (durations.append(1)) for every bounded relationship, so the stability metric was always 1.0 when any bounded relationship existed and 0 otherwise, never reflecting actual valid-time durations.
Stability now computes the mean valid-time duration in seconds ((valid_until - valid_from).total_seconds()) across relationships with both bounds set; unbounded/half-open intervals are skipped and non-positive intervals clamped to 0. Adds unit tests and a CHANGELOG entry.
Co-authored-by: 江俊杰 <jiangjunjie.37@jd.com>
* fix(dedup): never merge entities with different explicit types (fixes#1137)
The duplicate candidate confidence scoring only rewarded same-type pairs
but never penalized different-type pairs, so a Person 'Alice' and an
Organization 'Acme' (different id, type, and name) passed the confidence
threshold and were merged, silently dropping one entity. Add a type guard:
when both entities carry a non-empty type and they differ, the pair is
never a duplicate candidate (confidence 0, reason 'type_mismatch').
Untyped entities and genuinely duplicate same-type pairs keep their
previous behavior. Regression tests cover all three cases.
* fix(dedup): honor Entity.type and exclude mismatch structurally (review fixes)
Two gaps from code review (#1149):
1. _get_entity_value mapped object 'type' exclusively to .label, which
Entity objects never have — their type lives on .type. The mismatch
guard therefore never saw the type of Entity objects, and differently
typed objects could still merge. Read .type first, fall back to .label.
2. The mismatch branch returned a normal candidate with confidence 0.0,
but detection filters with >= confidence_threshold, and 0.0 is a
documented valid threshold, so mismatches slipped through. Exclude
type_mismatch candidates structurally at both filter sites regardless
of threshold.
Adds tests for Entity objects with different types and for
confidence_threshold=0.0. 94 dedup tests pass.
---------
* fix(reasoning): refuse SPARQL query execution instead of returning empty results (#1083)
SPARQLReasoner.execute_query() never executed the query: both branches
returned an empty SPARQLQueryResult, with or without a triplet store, so
callers that trust an empty result as "no matches" silently drew wrong
conclusions. Until a real triplet-store execution path lands, the method
raises NotImplementedError with an explanation, per the issue's
suggestion. The dead cache/inference scaffolding after the execution
point is removed along with it.
Co-Authored-By: Claude <noreply@anthropic.com>
* docs(reasoning): align execute_query() docs with the NotImplementedError contract (#1087)
Review feedback: the docstring still carried a "Returns" section and the
reasoning guide showed execute_query() returning bindings, both of which
now mislead. The docstring documents Raises only, the guide demonstrates
expand_query() and points to rdflib for execution until the triplet-store
path lands, and query_cache/clear_cache() are marked as reserved for that
future execution path.
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
* fix(utils): bound caller-controlled keys in validation error messages (#1001)
_require_recognized_keys() and _require_nothing_dropped() interpolated
supplied keys directly into ValidationError messages, so a megabyte-long
key produced a megabyte-long exception and, through the export wrappers
that log the full exception, an equally large log entry. Keys are now
rendered through _truncate_key(), which bounds the display at 64
characters with an ellipsis; the supplied payload is never modified.
Co-Authored-By: Claude <noreply@anthropic.com>
* fix(utils): bound the count of keys shown in validation error messages (#1001)
Review feedback: per-key truncation did not bound the number of keys
shown, so a payload carrying many short unknown keys could still size the
message (and the log entry that records it). _truncate_key_list() caps
the display at 8 keys and appends "and N more", keeping the message
actionable without letting the payload size it.
Co-Authored-By: Claude <noreply@anthropic.com>
---------
Co-authored-by: Claude <noreply@anthropic.com>
Convert_units() was validating categories on raw input like "kg" or "ft"
instead of the normalized unit name, so aliases got checked against a
category list that only has canonical names in it. Any alias-based
conversion that should've worked just raised ValidationError instead.
Fixed by normalizing both units before the category check runs.
Also added foot/yard/mile/gallon to the alias map - they already had
conversion factors but weren't mapped to their canonical names, so they'd
still have failed even after the above fix.
Turned out there was a second bug hiding behind the first one: the category
check defaults both sides to None, and None == None is True, so two aliases
from different categories that neither resolved to a real category would
silently pass instead of raising. kg -> ft would just return a number
instead of erroring. Normalizing first fixes this too, since aliases now
resolve to their actual categories and the mismatch gets caught.
Added a regression test locking that second one down - kg->ft and gal->lb
now raise ValidationError instead of silently converting.
Fixes#931.
Docker build was broken on python:3.14-slim because gensim doesn't ship a
3.14 wheel yet (typical of bleeding edge Python), so pip
tries to compile it from source and there's no gcc in the slim image.
gensim's a core dependency so every build hit this.
Went back to 3.13 instead of installing a compiler : simpler, and 3.14 was
just a jump from an automated bump PR anyway.
Fixes#1025.
* test(visualization): isolate optional dependency mocks
* test(visualization): stop requiring Plotly in unit tests
Removing the global sys.modules stubs left the tests that patch
`...go.Bar`, or call a visualizer, with nothing standing in for the
module level `px` and `go` aliases. Those are None when Plotly is
missing, so patch resolution and _check_dependencies() both failed.
Add a helper that substitutes a double only for the aliases that are
None, leaving the real module in place when Plotly is installed.
---------
* test(ingest): track relationship provenance via ProvenanceManager
kg.ProvenanceTracker has no track_relationship and never did, so
patch.object raised AttributeError before the test body ran.
Closes#1055
* test(ingest): disambiguate relationship keys and pin provenance storage
Addresses review feedback on #1071.
---------
All four are in the branch that recognises an already-converted document,
which has to survive every shape JSON-LD allows rather than the one shape
Semantica happens to produce.
A knowledge graph carrying a context of its own took the already-JSON-LD
branch and skipped its own conversion, leaving entity ids, relationship
endpoints, types and confidences as raw keys. The entities/relationships
test now runs first, and a converted document never has those keys, so the
double-conversion guard is unaffected.
A context that is a URL or an array cannot be merged key by key, and was
being dropped in favour of Semantica's defaults, silently changing how every
term expands. Both are kept as an array now, the caller's winning, which is
the same precedence the dictionary branch already used. An explicit null is
left alone on purpose: in an array it resets the active context and would
take the semantica prefix with it.
@graph may be a single node object as well as an array. list() on a
dictionary yields its keys, so an object-valued graph was replaced by a list
of strings.
A caller may hand us a document that is deliberately a named graph. That name
is theirs to keep, so it is no longer flattened; it is nested one level and
the export's own provenance goes beside it, in the default graph, where a
plain reader can see it.
Four tests, one per case, all failing before this commit.
Mohd Kaif