Card: the media dataset is now MLL-Lab/embodied-exam-data

README.md

@@ -18,7 +18,7 @@ reads only the highest `phaseN/` folder of a task (its DAG with its own trajecto
   two fix rounds plus a confirm round; files still disputed after that carry `review.status: "disputed"`.
 - Task repository: embodied-first-exam commit `4c6d01b9990e3b78ddb620bbd237932b3696f60e`.
 - Phase 1: two runs per task (one success when there is one, plus a failure of another model; runs with a video first).
-  Run records and videos: dataset `MLL-Lab/embodied-exam-media`, `runs/<runId>`.
+  Run records and videos: dataset `MLL-Lab/embodied-exam-data`, `runs/<runId>`.
 - Phase 1 complete: every task of the run passed validation and is listed below. Status: 331 tasks (3 pilot, 328 full run), 662 trajectories.
 
 ## Layout
@@ -382,7 +382,7 @@ reads only the highest `phaseN/` folder of a task (its DAG with its own trajecto
   (oracle) when its DAG was written stays that task's oracle. Runs without a graded video are labelled from the
   log only. Status: 5,780 of the 5,780 remaining runs labelled and uploaded (complete).
 - Run catalog: built from the run index of the dataset `MLL-Lab/embodied-exam-runs` (the run viewer's `run.json`
-  files); videos as in phase 1 from `MLL-Lab/embodied-exam-media`, `runs/<runId>/replay.mp4`. Some picked runs and
+  files); videos as in phase 1 from `MLL-Lab/embodied-exam-data`, `runs/<runId>/replay.mp4`. Some picked runs and
   tasks are newer than the catalog shipped with the labelling interface, so importing them needs a catalog refreshed
   from that run index.
 - The importer prefers the highest phase: when a task is under `phase1/` and `phase2/`, only `phase2/<suite>/<task>/`