Merges the full hardened stack (up through #791 drawer-grep) and turns
fact_checker from "dead code hidden behind bare except" into an
actually-working offline contradiction detector with tests.

## Dead paths the PR body advertised but the code never executed

Both buried by a single outer ``except Exception: pass``:

  * ``kg.query(subject)`` — ``KnowledgeGraph`` has no ``query()`` method;
    it has ``query_entity()``. The attribute error was silently swallowed
    and the entire KG branch always returned ``[]``. Now using
    ``kg.query_entity(subject, direction="outgoing")`` with proper
    handling of the ``predicate``/``object``/``current``/``valid_to``
    fields the real API returns.
  * ``KnowledgeGraph(palace_path=palace_path)`` — the constructor's only
    kwarg is ``db_path``. Passing ``palace_path`` raised TypeError,
    silently swallowed. Now computing the db_path correctly from
    ``<palace>/knowledge_graph.sqlite3``, matching the convention the
    MCP server already uses.

## Contradiction logic rewritten

The previous ``if kg_pred in claim and fact.object not in claim`` only
fired when text used the SAME predicate word as the KG fact — the exact
opposite of the stated use case ("Bob is Alice's brother" when KG says
husband" would NOT have fired). Replaced with a proper parse → lookup
→ compare pipeline:

  * ``_extract_claims`` parses two surface forms ("X is Y's Z" and
    "X's Z is Y") into ``(subject, predicate, object)`` triples.
  * ``_check_kg_contradictions`` pulls the subject's outgoing facts
    and flags two classes:
      - ``relationship_mismatch`` when a current KG fact matches the
        same ``(subject, object)`` pair but with a different predicate.
      - ``stale_fact`` when the exact triple exists but is
        ``valid_to``-closed in the past.
  * Stale-fact detection is now implemented (the PR body claimed it;
    the old code silently didn't implement it).

## Performance fix — O(n²) → O(mentioned × n)

``_check_entity_confusion`` previously computed Levenshtein for every
pair of registered names on every ``check_text`` call. For 1,000
registered names that's ~500K edit-distance calls per hook invocation.
Now we first identify which registry names actually appear in the text
(single regex scan), then only compute edit distance between mentioned
and unmentioned names. Pinned by a test that asserts <200ms on a 500-
name registry with zero mentions.

Also: when *both* similar names are mentioned in the text, we no
longer flag them — the user clearly knows they're different people.

## Shared entity-registry loader

``mempalace/miner.py`` already had an mtime-cached loader for
``~/.mempalace/known_entities.json``. fact_checker had a duplicate
implementation that leaked file handles and ignored caching. Extended
miner's cache to expose both the flat set (``_load_known_entities``)
and the raw category dict (``_load_known_entities_raw``); fact_checker
now imports the latter. No more double disk reads, no more handle leak.

## Tests — 24 cases in tests/test_fact_checker.py

All three detection paths + both dead-code regressions:
  * ``test_kg_init_uses_db_path_not_palace_path_kwarg`` — pins the
    correct KG constructor signature so the ``palace_path=`` bug can't
    come back.
  * ``test_relationship_mismatch_detected`` — the headline example from
    the PR body now actually fires.
  * ``test_stale_fact_detected`` — valid_to-closed triple is flagged.
  * ``test_current_fact_same_triple_is_not_flagged`` — no false positive
    on a still-valid match.
  * ``test_performance_bounded_by_mentioned_names`` — 500-name registry,
    zero mentions, <200ms. Regression for the O(n²) blowup.
  * ``test_no_false_positive_when_both_names_mentioned`` — Mila and
    Milla in the same text is fine.
  * Plus claim extraction, flatten_names shapes, CLI exit code, empty
    text handling, missing-palace graceful fallback, registry-dict
    shape support.

785/785 suite pass. ruff + format clean on CI-pinned 0.4.x.