feat(pipeline): implement parliamentary embedding pipeline MVP

- Add 4 migration files: mp_votes, mp_metadata, svd_vectors, fused_embeddings
- Extend database.py with 5 new helper methods and table init
- Add pipeline/ package: extract_mp_votes, fetch_mp_metadata, text_pipeline,
  svd_pipeline (with Procrustes alignment), fusion
- Add full test suite (17 tests) covering all pipeline modules and migrations
- Fix Procrustes alignment bug: scipy scale is a norm value, not a multiplier
- Fix DuckDB date type handling in test assertions (datetime.date vs string)
- Remove duckdb.py shim; tests now run against real duckdb + scipy via uv

Ref: thoughts/shared/plans/2026-03-21-parliamentary-embedding-pipeline-plan.md

src/types/motion_types.py

@@ -0,0 +1,35 @@
+"""Motion-related simple types and JSON helpers.
+
+Decision: MotionId is an alias for str for simplicity.
+"""
+
+from dataclasses import dataclass, asdict
+from typing import List
+import json
+
+MotionId = str
+Embedding = List[float]
+
+
+@dataclass
+class SimilarityNeighbor:
+    motion_id: MotionId
+    score: float
+
+
+def to_json(neighbors: List[SimilarityNeighbor]) -> str:
+    """Serialize a list of SimilarityNeighbor to a JSON string.
+
+    The format is a JSON list of objects with keys 'motion_id' and 'score'.
+    """
+    list_of_dicts = [asdict(n) for n in neighbors]
+    return json.dumps(list_of_dicts)
+
+
+def from_json(json_str: str) -> List[SimilarityNeighbor]:
+    """Deserialize a JSON string (list of dicts) into SimilarityNeighbor list."""
+    parsed = json.loads(json_str)
+    return [
+        SimilarityNeighbor(motion_id=item["motion_id"], score=float(item["score"]))
+        for item in parsed
+    ]