Improve extraction accuracy with speaker role inference

Add a SPEAKER ROLES section to the GPT-4o-mini prompt teaching it to
distinguish dispatch voice (names a unit then gives assignment + address)
from unit voice (opens with own callsign + brief status). Applied to
location attribution (dispatch-provided address beats unit position report)
and unit extraction (dispatched units vs. acknowledging units). No extra
API calls — purely prompt-level reasoning on the existing transcript.

README.md

@@ -245,9 +245,13 @@ Edge node ──► audio upload    ──► GCS storage
                                         │
                                         ▼
                                [2] INTELLIGENCE EXTRACTION (GPT-4o-mini)
-                                   Scene detection, entity extraction:
-                                   tags, incident_type, location, units,
-                                   vehicles, severity, resolved flag
+                                   Scene detection — splits multi-incident recordings
+                                   Speaker role inference — dispatch vs. unit patterns
+                                   used to correctly attribute locations (dispatch-
+                                   provided address vs. unit position report) and
+                                   units (being dispatched vs. acknowledging)
+                                   Entity extraction: tags, incident_type, location,
+                                   units, vehicles, severity, resolved flag
                                    + geocoding (Google Maps)
                                    + embedding (text-embedding-3-small)
                                    → CallRecord.tags, .location, .units, etc.