phase 17: pass all tracked tickers to extractor, soften prompt for macro-to-company relevance

services/extractor/main.py

@@ -88,10 +88,12 @@ async def main() -> None:
                 company_id_map = await _build_company_id_map(pool)
 
             try:
+                # Pass all tracked tickers so the model can identify any mentioned companies
+                all_tickers = list(company_id_map.keys()) if company_id_map else ([ticker] if ticker else None)
                 extraction_response = await ollama.extract(
                     text,
                     document_id=document_id,
-                    known_tickers=[ticker] if ticker else None,
+                    known_tickers=all_tickers,
                 )
                 result = await persist_extraction(
                     pool=pool,

services/extractor/prompts.py

@@ -102,9 +102,12 @@ def build_extraction_prompt(
     if known_tickers:
         tickers_str = ", ".join(known_tickers)
         ticker_hint = (
-            f"\nThe following tickers may be referenced in this document: {tickers_str}\n"
-            "Only include a ticker in your output if the document actually discusses that company. "
-            "Do NOT include a ticker just because it appears in this hint."
+            f"\nTracked tickers: {tickers_str}\n"
+            "If the document discusses market conditions, sectors, or themes that directly affect "
+            "any of these companies, include those companies with appropriate sentiment and impact scores. "
+            "A macro article about oil prices IS relevant to energy companies like XOM. "
+            "A tech sector article IS relevant to AAPL, MSFT, NVDA, etc. "
+            "Use your judgment — but only include companies where the connection is clear from the text."
         )
 
     schema_str = json.dumps(EXTRACTION_JSON_SCHEMA, indent=2)