diff --git a/klausur-service/backend/grid_editor_api.py b/klausur-service/backend/grid_editor_api.py
index 75076af..cd804be 100644
--- a/klausur-service/backend/grid_editor_api.py
+++ b/klausur-service/backend/grid_editor_api.py
@@ -1588,21 +1588,32 @@ async def _build_grid_core(session_id: str, session: dict) -> dict:
     all_cells = [cell for z in zones_data for cell in z.get("cells", [])]
     total_cols = sum(len(z.get("columns", [])) for z in zones_data)
     if total_cols >= 3:
-        # Find which col_type has the longest average text → English headwords
+        # Find the column that contains IPA brackets → English headwords.
+        # Count cells with bracket patterns per col_type.  The column with
+        # the most brackets is the headword column (IPA sits after or below
+        # headwords).  Falls back to longest-average if no brackets found.
+        col_bracket_count: Dict[str, int] = {}
         col_avg_len: Dict[str, List[int]] = {}
         for cell in all_cells:
             ct = cell.get("col_type", "")
-            txt = cell.get("text", "")
+            txt = cell.get("text", "") or ""
             col_avg_len.setdefault(ct, []).append(len(txt))
+            if ct.startswith("column_") and '[' in txt:
+                col_bracket_count[ct] = col_bracket_count.get(ct, 0) + 1
+        # Pick column with most bracket IPA patterns
         en_col_type = None
-        best_avg = 0
-        for ct, lengths in col_avg_len.items():
-            if not ct.startswith("column_"):
-                continue
-            avg = sum(lengths) / len(lengths) if lengths else 0
-            if avg > best_avg:
-                best_avg = avg
-                en_col_type = ct
+        if col_bracket_count:
+            en_col_type = max(col_bracket_count, key=col_bracket_count.get)
+        else:
+            # Fallback: longest average text
+            best_avg = 0
+            for ct, lengths in col_avg_len.items():
+                if not ct.startswith("column_"):
+                    continue
+                avg = sum(lengths) / len(lengths) if lengths else 0
+                if avg > best_avg:
+                    best_avg = avg
+                    en_col_type = ct
         if en_col_type:
             for cell in all_cells:
                 if cell.get("col_type") == en_col_type: