refactor(ocr): extract _collapse_adjacent_markers helper and add CORRECTION_MARKER

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

ocr-service/confidence.py

@@ -6,6 +6,21 @@ THRESHOLD_DEFAULT = float(os.environ.get("OCR_CONFIDENCE_THRESHOLD", "0.3"))
 THRESHOLD_KURRENT = float(os.environ.get("OCR_CONFIDENCE_THRESHOLD_KURRENT", "0.5"))
 
 ILLEGIBLE_MARKER = "[unleserlich]"
+CORRECTION_MARKER = "[?]"
+
+
+def _collapse_adjacent_markers(tokens: list[str]) -> list[str]:
+    collapsed: list[str] = []
+    prev_was_marker = False
+    for token in tokens:
+        if token == ILLEGIBLE_MARKER:
+            if not prev_was_marker:
+                collapsed.append(token)
+            prev_was_marker = True
+        else:
+            collapsed.append(token)
+            prev_was_marker = False
+    return collapsed
 
 
 def get_threshold(script_type: str) -> float:
@@ -30,19 +45,14 @@ def apply_confidence_markers(words: list[dict], threshold: float | None = None)
     if threshold is None:
         threshold = THRESHOLD_DEFAULT
 
-    result: list[str] = []
-    prev_was_marker = False
-
+    tokens: list[str] = []
     for word in words:
         if word["confidence"] < threshold:
-            if not prev_was_marker:
-                result.append(ILLEGIBLE_MARKER)
-            prev_was_marker = True
+            tokens.append(ILLEGIBLE_MARKER)
         else:
-            result.append(word["text"])
-            prev_was_marker = False
+            tokens.append(word["text"])
 
-    return " ".join(result)
+    return " ".join(_collapse_adjacent_markers(tokens))
 
 
 def words_from_characters(prediction: str, confidences: list[float]) -> list[dict]: