feat: Intelligence Pipeline v3 — full implementation

Multi-stage evidence-grounded inference architecture replacing the
monolithic 9B model extraction pipeline. CPU-first specialist services
handle routine extraction while the 9B vLLM model is preserved for
semantic adjudication of ambiguous cases.

Key components:
- Capability-aware inference gateway (OpenAI-compatible + Ollama)
- Endpoint registry with DB migrations and REST API
- Sentence-aware document segmenter (property tests)
- Deterministic financial parsing with offset integrity
- Symbol resolution with ambiguity detection
- Specialist service (GLiNER2, dynamic batching, K8s deployment)
- Company-specific sentiment (FinBERT, calibration)
- Retrieval-based novelty and duplicate detection
- Confidence calibration pipeline
- Deterministic routing engine (property tests)
- 9B adjudication layer with VRAM gating
- Stock-specific impact model (features, labels, baseline, trained)
- Pipeline orchestrator (state machine, queues, leases, feature flags)
- Bounded parallelism (async workers, semaphore, load shedding)
- Observability (tracing, metrics, alerts)
- Compatibility adapter (v3→v2 golden mapping tests)
- Shadow/canary promotion framework
- Active learning and fine-tuning pipeline

Test results: 1,161 tests pass, ruff lint clean.
All 282 spec tasks completed.

services/intelligence_pipeline_v3/parsing/__init__.py

@@ -0,0 +1,26 @@
+"""Deterministic financial parsing for the v3 intelligence pipeline.
+
+This package provides regex-based detection of financial entities:
+- Ticker symbols ($AAPL, AAPL)
+- Currencies and money amounts ($123.45, €99, $94.9 billion)
+- Percentages (4%, -2.5%)
+- Basis points (25 basis points, 25bps)
+- Ranges ($10-$12)
+- EPS values ($1.52 per share)
+- Revenue figures
+- Dates and fiscal periods (Q1 2024, FY2025)
+
+Each match returns exact character offsets, literal text, and a normalized numeric value.
+"""
+
+from services.intelligence_pipeline_v3.parsing.financial_parser import FinancialParser
+from services.intelligence_pipeline_v3.parsing.models import CandidateType, ParsedCandidate, PeriodAnnotation
+from services.intelligence_pipeline_v3.parsing.normalizer import normalize_value
+
+__all__ = [
+    "CandidateType",
+    "FinancialParser",
+    "ParsedCandidate",
+    "PeriodAnnotation",
+    "normalize_value",
+]