Align watermark content with detector coverage

scripts/visible_groundtruth.py

@@ -1,6 +1,6 @@
-"""Consolidate the hand-labelled contact-sheet rounds into ONE ground-truth file.
+"""Consolidate the hand-labeled contact-sheet rounds into ONE ground-truth file.
 
-Ground truth is `uid -> the set of visible marks actually present`, hand-labelled
+Ground truth is `uid -> the set of visible marks actually present`, hand-labeled
 blind against contact sheets with a two-sided control in every round. Rounds so far:
 
   2026-07-18 text-mark/pill round : 423 cells (doubao / jimeng / jimeng_pill arms)
@@ -10,12 +10,12 @@ DATA SAFETY: treat the input dataset as sensitive. This script reads a gitignore
 dataset and writes a gitignored ground-truth file. Neither the images nor this
 output may be committed; only the harness is. See the repo CLAUDE.md.
 
-The labels record what the LABELLER SAW in the crop, one of:
+The labels record what the labeler saw in the crop, one of:
   doubao | jimeng | pill | sparkle | other_ai_label | none | uncertain
 `other_ai_label` is a real visible AI label from a vendor we do NOT have a mark for
 (千问 / 百度 / 星绘 / 抖音); it is NOT a positive for any registered mark, but it is
 also not "clean" -- it is exactly what the relaxed jimeng detector confuses.
-`uncertain` rows are EXCLUDED from scoring rather than coerced, so a labeller's
+`uncertain` rows are EXCLUDED from scoring rather than coerced, so a labeler's
 honest doubt never becomes a fabricated data point.
 """
 
@@ -32,7 +32,7 @@ SEEN_TO_MARK = {
     "pill": "jimeng_pill",
     "sparkle": "gemini",
 }
-# Which marks a crop centred on `key` lets the labeller rule on (same corner = visible
+# Which marks a crop centered on `key` lets the labeler rule on (same corner = visible
 # in the same crop). Doubao and Jimeng share the bottom-right corner.
 _ADJUDICATES = {
     "doubao": ("doubao", "jimeng"),
@@ -83,7 +83,7 @@ def main() -> None:
         type=Path,
         nargs="?",
         default=Path(".local-eval/textmark-relaxation"),
-        help="Directory containing the blinded labelling rounds",
+        help="Directory containing the blinded labeling rounds",
     )
     root = parser.parse_args().root
     out = root / "groundtruth.jsonl"
@@ -105,8 +105,8 @@ def main() -> None:
                 m["uid"],
                 {"uid": m["uid"], "path": m["path"], "present": [], "seen": [], "rounds": [], "adjudicated": []},
             )
-            # ADJUDICATION SCOPE -- load-bearing. A crop centred on one mark only lets
-            # the labeller rule on marks visible IN THAT CROP. A pill crop (top-left)
+            # ADJUDICATION SCOPE -- load-bearing. A crop centered on one mark only lets
+            # the labeler rule on marks visible IN THAT CROP. A pill crop (top-left)
             # says nothing about a bottom-right wordmark, so scoring jimeng against a
             # pill-round image would book real detections as false fires (~61% of pills
             # carry a wordmark). Bottom-right marks co-adjudicate each other: one crop