Implement Semantic Consolidator V0

- add deterministic canonicalization support for extraction items
- add facts-only semantic consolidation using local Ollama
- preserve source evidence and validate complete fact coverage
- add conservative merge rules and non-LLM tests
- record the first validated real-life consolidation benchmark
- document current scope, limitations and next evaluation step

docs/pipeline.md

@@ -135,7 +135,15 @@ Deterministic
 
 ## Current Status
 
-Planned
+Implemented as Canonicalizer V1.
+
+CLI:
+
+```text
+PYTHONPATH=src .venv/bin/python -m meeting_lab.consolidation.canonicalize \
+  samples/whisper/meeting_speech_cleaned_chunks \
+  -o /tmp/canonicalized_extractions.json
+```
 
 ---
 
@@ -231,7 +239,7 @@ LLM
 
 ## Current Status
 
-Planned
+Implemented as Canonicalizer V1.
 
 ---
 
@@ -325,16 +333,23 @@ Canonicalized extraction objects.
 
 ## Output
 
-Canonical Meeting Knowledge.
+Semantic Consolidator V0 output is `consolidated_extractions.json` with fact
+groups and unchanged non-fact items.
+
+Future broader semantic consolidation should produce Canonical Meeting
+Knowledge.
 
 ## Responsibilities
 
-- Merge semantically equivalent statements
-- Group content by topic
+- V0: merge semantically equivalent fact items only
+- V0: preserve all non-fact categories unchanged
+- V0: validate that every source fact ID appears exactly once
+- Future: merge semantically equivalent statements across categories
+- Future: group content by topic
 - Preserve evidence from all contributing chunks
-- Mark contradictions and uncertainty
-- Separate durable information from transient discussion
-- Reconcile category shifts where supported by evidence
+- Future: mark contradictions and uncertainty
+- Future: separate durable information from transient discussion
+- Future: reconcile category shifts where supported by evidence
 
 ## Must Not
 
@@ -348,7 +363,9 @@ Local LLM, with deterministic pre/post-processing where useful.
 
 ## Current Status
 
-Planned
+Semantic Consolidator V0 is implemented and experimentally validated for
+facts-only conservative duplicate detection. Broader semantic consolidation and
+Canonical Meeting Knowledge generation remain planned.
 
 ---
 
@@ -507,16 +524,18 @@ A processing stage may be replaced by another implementation as long as it prese
 
 ⬜ Specialized Extraction
 
-⬜ Deterministic Canonicalization
+✔ Deterministic Canonicalization
 
-⬜ Semantic Consolidation
+✅ Semantic Consolidation V0 - facts-only duplicate detection
 
 ⬜ Canonical Meeting Knowledge
 
 ⬜ Output View Rendering
 ```
 
-The immediate architecture focus is the Deterministic Canonicalizer followed by
-the Semantic Consolidator. These stages preserve source evidence, recover
-global context from independent chunk extractions and prepare Canonical Meeting
-Knowledge for parallel Output View rendering.
+The immediate evaluation focus is using the Semantic Consolidator V0 output as
+input for the unchanged Working Protocol renderer. Canonicalizer V1 now
+preserves source evidence, and Semantic Consolidator V0 conservatively merges
+semantically equivalent fact items. Broader semantic consolidation should later
+recover global context from independent chunk extractions and prepare Canonical
+Meeting Knowledge for parallel Output View rendering.