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README.md

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 CRONOS-Benchmark is a controlled, synthetic benchmark for evaluating **counterfactual physical consistency** in video world models. It tests whether generative video models correctly simulate three fundamental physical event types — **object falling**, **object collision**, and **object occlusion** — across diverse scenes, objects, and viewpoints.
 
-Each sequence provides ground-truth RGB frames, depth maps, and segmentation masks, along with a 5-frame conditioning clip, enabling standardised evaluation of any video generation model that accepts image or video conditioning.
+Each sequence provides ground-truth RGB frames, depth maps, and segmentation masks, along with a 5-frame conditioning clip and a `metadata.json` file, enabling standardised evaluation of any video generation model that accepts image or video conditioning.
 
 ## Dataset Details
 
@@ -65,9 +65,10 @@ dataset/
                     ├── rgb/          # 90 × frame_XXXX.jpg  (1920×1080, colour)
                     ├── depth/        # 90 × frame_XXXX.jpg  (1920×1080, depth)
                     ├── mask/         # 90 × frame_XXXX.jpg  (1920×1080, binary)
-                    └── movies/
-                        ├── complete.mp4        # full 90-frame sequence
-                        └── conditioning_5.mp4  # first 5 frames (conditioning input)
+                    ├── movies/
+                    │   ├── complete.mp4        # full 90-frame sequence
+                    │   └── conditioning_5.mp4  # first 5 frames (conditioning input)
+                    └── metadata.json           # sequence metadata and text prompt
 ```
 
 ### Modalities
@@ -79,6 +80,7 @@ dataset/
 | Mask | JPEG | 1920 × 1080 | Per object segmentation mask |
 | `complete.mp4` | MP4 | 1920 × 1080 | Full ground-truth sequence (90 frames) |
 | `conditioning_5.mp4` | MP4 | 1920 × 1080 | First 5 frames, used as model conditioning input |
+| `metadata.json` | JSON | — | Sequence identifiers (`event`, `scene`, `object`, `appearance`, `view`) and a natural-language `prompt` describing the expected physical event |
 
 ### Dataset statistics
 

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