feat: robust metric extraction with confidence score and proof snippets

- fixed Year-Prefix Bug in MetricParser
- added metric_confidence and metric_proof_text to database
- added Entity-Check and Annual-Priority to LLM prompt
- improved UI: added confidence traffic light and mouse-over proof tooltip
- restored missing API endpoints (create, bulk, wiki-override)

company-explorer/backend/database.py

@@ -50,6 +50,9 @@ class Company(Base):
     standardized_metric_value = Column(Float, nullable=True) # e.g., 4500.0
     standardized_metric_unit = Column(String, nullable=True) # e.g., "m²"
     metric_source = Column(String, nullable=True)            # "website", "wikipedia", "serpapi"
+    metric_proof_text = Column(Text, nullable=True)          # Snippet showing the value (e.g. "2,0 Mio Besucher (2020)")
+    metric_confidence = Column(Float, nullable=True)         # 0.0 - 1.0
+    metric_confidence_reason = Column(Text, nullable=True)   # Why is it high/low?
     
     # Relationships
     signals = relationship("Signal", back_populates="company", cascade="all, delete-orphan")