flatten event_verification

CHANGELOG.md

@@ -2,6 +2,18 @@
 
 All notable changes to **`nvidia/PhysicalAI-VANTAGE-Bench`** on Hugging Face.
 
+## 2026-05-27
+- **`data/event_verification/` flattened** to match the `vqa/` and
+  `temporal_localization/` layout. The `filtered/.../{metropolis,tailgating,warehouse_near_miss}`
+  subtree was removed; all 163 videos now live directly under
+  `data/event_verification/videos/`, and the four annotation JSONs were
+  moved + renamed to
+  `data/event_verification/data_jsons/annotations/{metropolis_event_verification,tailgating_location_a,tailgating_location_b,warehouse_near_miss}.json`.
+  Each `bcq[].video` is now the basename (e.g. `example.mp4`) and each
+  `bcq[].id` is the stem (e.g. `example`); all other fields, entry
+  order, and counts (163 total) are preserved. The `configs:` glob in
+  the top-level README is updated accordingly.
+
 ## 2026-05-19
 
 - README YAML updated with a `configs:` block so the HF dataset viewer

README.md

@@ -14,7 +14,7 @@ configs:
 - config_name: event_verification
   data_files:
   - split: test
-    path: data/event_verification/filtered/**/*.json
+    path: data/event_verification/data_jsons/annotations/*.json
 - config_name: referring
   data_files:
   - split: test

data/README.md

@@ -15,10 +15,8 @@ data/
 │   ├── prompt.json
 │   └── *.mp4
 ├── event_verification/           # Binary event classification
-│   └── filtered/
-│       ├── metropolis_event_verification/{*.mp4, test_annotation.json}
-│       ├── tailgating/{location_a, location_b}/{*.mp4, test_annotation.json}
-│       └── warehouse_near_miss/{*.mp4, test_annotations.json}
+│   ├── *.mp4 (under videos/)
+│   └── data_jsons/annotations/*.json
 ├── pointing/                     # 2D spatial pointing
 │   └── Vantage2DPointing.tsv
 ├── referring/                    # 2D referring expressions
@@ -51,9 +49,14 @@ Per-entry questions in `vqa/data_jsons/annotations/*.json`. Each entry has `{q_u
 Per-entry questions in `temporal_localization/data_jsons/annotations/*.json`. Each entry has `{vid, question_id, question, duration, …}`; the `answer` timestamps are removed.
 
 ### `event_verification/` — Binary Event Verification
-All four annotation files share a unified schema:
-`{"bcq": [{id, video, system_prompt, question}, …]}`. The binary `answer`
-is removed.
+Per-entry questions in `event_verification/data_jsons/annotations/*.json`
+(four files: `metropolis_event_verification.json`,
+`tailgating_location_a.json`, `tailgating_location_b.json`,
+`warehouse_near_miss.json`). All four share a unified schema:
+`{"bcq": [{id, video, system_prompt, question}, …]}` where `video` is the
+basename (e.g. `example.mp4`) and `id` is the stem (e.g. `example`),
+resolving against `event_verification/videos/`. The binary `answer` is
+removed.
 
 ### `pointing/` — 2D Spatial Pointing
 `Vantage2DPointing.tsv` — tab-separated. Each row carries the question and multiple-choice options; the last two ground-truth columns are dropped.

data/event_verification/{filtered/metropolis_event_verification/test_annotation.json → data_jsons/annotations/metropolis_event_verification.json}

@@ -1,404 +1,404 @@
 {
   "bcq": [
     {
-      "id": "traffic_chunks/LUPZNgg5idk_13",
-      "video": "traffic_chunks/LUPZNgg5idk_13.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "LUPZNgg5idk_13",
+      "video": "LUPZNgg5idk_13.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/IpgfZf6Y2BE_14",
-      "video": "traffic_chunks/IpgfZf6Y2BE_14.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "IpgfZf6Y2BE_14",
+      "video": "IpgfZf6Y2BE_14.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/IpgfZf6Y2BE_15",
-      "video": "traffic_chunks/IpgfZf6Y2BE_15.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "IpgfZf6Y2BE_15",
+      "video": "IpgfZf6Y2BE_15.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/NOALQmAB4yE_16",
-      "video": "traffic_chunks/NOALQmAB4yE_16.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "NOALQmAB4yE_16",
+      "video": "NOALQmAB4yE_16.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a vehicle collide with pedestrian?"
     },
     {
-      "id": "traffic_chunks/SEb7p5oszeM_17",
-      "video": "traffic_chunks/SEb7p5oszeM_17.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "SEb7p5oszeM_17",
+      "video": "SEb7p5oszeM_17.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a vehicle collide with a cyclist?"
     },
     {
-      "id": "traffic_chunks/SEb7p5oszeM_18",
-      "video": "traffic_chunks/SEb7p5oszeM_18.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "SEb7p5oszeM_18",
+      "video": "SEb7p5oszeM_18.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a vehicle collide with a pedestrian?"
     },
     {
-      "id": "traffic_chunks/MmsgbcpWn-k_19",
-      "video": "traffic_chunks/MmsgbcpWn-k_19.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "MmsgbcpWn-k_19",
+      "video": "MmsgbcpWn-k_19.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/MmsgbcpWn-k_20",
-      "video": "traffic_chunks/MmsgbcpWn-k_20.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "MmsgbcpWn-k_20",
+      "video": "MmsgbcpWn-k_20.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/MmsgbcpWn-k_21",
-      "video": "traffic_chunks/MmsgbcpWn-k_21.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "MmsgbcpWn-k_21",
+      "video": "MmsgbcpWn-k_21.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "traffic_chunks/NOALQmAB4yE_24",
-      "video": "traffic_chunks/NOALQmAB4yE_24.mp4",
-      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is \u201clikely\u201d if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
+      "id": "NOALQmAB4yE_24",
+      "video": "NOALQmAB4yE_24.mp4",
+      "system_prompt": "You are a traffic monitoring system analyzing video of a street. Determine if a collision between vehicles, or vehicle and pedestrian or vehicle and cyclist has likely occurred.\nThe clip may not show the exact moment of impact, so use post-event evidence such as:\n- Vehicles in contact or showing visible damage (dents, debris, smoke, broken parts).\n- Pedestrian or cyclist on the ground, struck, or showing clear signs of impact or distress.. \n- Abnormal positions (intersecting, facing opposite directions, one against the side/rear of another).\n- Stationary vehicles remaining in contact or stopped in unnatural alignment.\n- Behavior inconsistent with normal driving (sudden halt, failure to separate, blocked motion).\n- Other unusual signs (e.g., airbags, leaking fluids, shattered glass) can also support the conclusion.\nA collision is “likely” if two or more independent cues strongly indicate impact, even if the collision itself is not shown. If evidence is weak or ambiguous, do not assume a collision.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a collision occur between two or more vehicles?"
     },
     {
-      "id": "safety_chunks/evs_134db13b21",
-      "video": "safety_chunks/evs_134db13b21.mp4",
+      "id": "evs_134db13b21",
+      "video": "evs_134db13b21.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_99c1cd175d",
-      "video": "safety_chunks/evs_99c1cd175d.mp4",
+      "id": "evs_99c1cd175d",
+      "video": "evs_99c1cd175d.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_8cc3cd0258",
-      "video": "safety_chunks/evs_8cc3cd0258.mp4",
+      "id": "evs_8cc3cd0258",
+      "video": "evs_8cc3cd0258.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_bc929d97da",
-      "video": "safety_chunks/evs_bc929d97da.mp4",
+      "id": "evs_bc929d97da",
+      "video": "evs_bc929d97da.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_d897e4ada3",
-      "video": "safety_chunks/evs_d897e4ada3.mp4",
+      "id": "evs_d897e4ada3",
+      "video": "evs_d897e4ada3.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_c3e684b820",
-      "video": "safety_chunks/evs_c3e684b820.mp4",
+      "id": "evs_c3e684b820",
+      "video": "evs_c3e684b820.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_17560f2666",
-      "video": "safety_chunks/evs_17560f2666.mp4",
+      "id": "evs_17560f2666",
+      "video": "evs_17560f2666.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_0f0c53aa1c",
-      "video": "safety_chunks/evs_0f0c53aa1c.mp4",
+      "id": "evs_0f0c53aa1c",
+      "video": "evs_0f0c53aa1c.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_405dd1e5f8",
-      "video": "safety_chunks/evs_405dd1e5f8.mp4",
+      "id": "evs_405dd1e5f8",
+      "video": "evs_405dd1e5f8.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_8f5ae5b865",
-      "video": "safety_chunks/evs_8f5ae5b865.mp4",
+      "id": "evs_8f5ae5b865",
+      "video": "evs_8f5ae5b865.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_50815b9c8c",
-      "video": "safety_chunks/evs_50815b9c8c.mp4",
+      "id": "evs_50815b9c8c",
+      "video": "evs_50815b9c8c.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/tailgating_13",
-      "video": "safety_chunks/tailgating_13.mp4",
+      "id": "tailgating_13",
+      "video": "tailgating_13.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_866549be90",
-      "video": "safety_chunks/evs_866549be90.mp4",
+      "id": "evs_866549be90",
+      "video": "evs_866549be90.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_e5ccfbd6bd",
-      "video": "safety_chunks/evs_e5ccfbd6bd.mp4",
+      "id": "evs_e5ccfbd6bd",
+      "video": "evs_e5ccfbd6bd.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_d2523c5c64",
-      "video": "safety_chunks/evs_d2523c5c64.mp4",
+      "id": "evs_d2523c5c64",
+      "video": "evs_d2523c5c64.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_f717d6dd57",
-      "video": "safety_chunks/evs_f717d6dd57.mp4",
+      "id": "evs_f717d6dd57",
+      "video": "evs_f717d6dd57.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_110cbe0aac",
-      "video": "safety_chunks/evs_110cbe0aac.mp4",
+      "id": "evs_110cbe0aac",
+      "video": "evs_110cbe0aac.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is anyone fighting?"
     },
     {
-      "id": "safety_chunks/evs_8e472b1db0",
-      "video": "safety_chunks/evs_8e472b1db0.mp4",
+      "id": "evs_8e472b1db0",
+      "video": "evs_8e472b1db0.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is anyone fighting?"
     },
     {
-      "id": "safety_chunks/evs_abf9d9bc50",
-      "video": "safety_chunks/evs_abf9d9bc50.mp4",
+      "id": "evs_abf9d9bc50",
+      "video": "evs_abf9d9bc50.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_c950abf04f",
-      "video": "safety_chunks/evs_c950abf04f.mp4",
+      "id": "evs_c950abf04f",
+      "video": "evs_c950abf04f.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/Security_3_22",
-      "video": "safety_chunks/Security_3_22.mp4",
+      "id": "Security_3_22",
+      "video": "Security_3_22.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is anyone fighting?"
     },
     {
-      "id": "safety_chunks/Security_2_23",
-      "video": "safety_chunks/Security_2_23.mp4",
+      "id": "Security_2_23",
+      "video": "Security_2_23.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/Security_2_24",
-      "video": "safety_chunks/Security_2_24.mp4",
+      "id": "Security_2_24",
+      "video": "Security_2_24.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/Security_2_25",
-      "video": "safety_chunks/Security_2_25.mp4",
+      "id": "Security_2_25",
+      "video": "Security_2_25.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Entering is from left to right and exiting is from right to left, is anyone exiting with a cart full of equipment?"
     },
     {
-      "id": "safety_chunks/Security_2_26",
-      "video": "safety_chunks/Security_2_26.mp4",
+      "id": "Security_2_26",
+      "video": "Security_2_26.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Entering is from left to right and exiting is from right to left, is anyone entering with a cart full of equipment?"
     },
     {
-      "id": "safety_chunks/GX010011_Clip_8_27",
-      "video": "safety_chunks/GX010011_Clip_8_27.mp4",
+      "id": "GX010011_Clip_8_27",
+      "video": "GX010011_Clip_8_27.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the hallway overcrowded?"
     },
     {
-      "id": "safety_chunks/GX010011_Clip_9_28",
-      "video": "safety_chunks/GX010011_Clip_9_28.mp4",
+      "id": "GX010011_Clip_9_28",
+      "video": "GX010011_Clip_9_28.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does everyone scan a badge to enter the room?"
     },
     {
-      "id": "safety_chunks/evs_f262e9ed6a",
-      "video": "safety_chunks/evs_f262e9ed6a.mp4",
+      "id": "evs_f262e9ed6a",
+      "video": "evs_f262e9ed6a.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_48a0587066",
-      "video": "safety_chunks/evs_48a0587066.mp4",
+      "id": "evs_48a0587066",
+      "video": "evs_48a0587066.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "safety_chunks/evs_191151ccf4",
-      "video": "safety_chunks/evs_191151ccf4.mp4",
+      "id": "evs_191151ccf4",
+      "video": "evs_191151ccf4.mp4",
       "system_prompt": "You are a security monitoring system analyzing video of a access gate and hallways. \n\nGate Monitoring:\nWhen monitoring access gate, people are required to badge, the gate unlocks, and they enter. Determine whether a tailgating/piggybacking event has likely occurred (i.e., one or more people enter on a single authorization without individually badging).\nThe video clip shows the badge reader. Infer from post-event evidence such as:\n- Single gate-open event while multiple people pass through before the gate closes.\n- A follower enters closely behind the badged person (minimal gap in time or distance) without stopping at the reader or making a clear badging gesture.\n- The gate is held open/propped, or gate-open duration is longer than typical for a single entrant.\n- Multiple people cross the threshold during one gate cycle (gate does not close between them).\n- The leader looks back/holds the door while the follower does not badge.\n\nHallway Monitoring: \n- At the hallways look for fights and overcrowding.\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did a person tailgate through the access gate without badging?"
     },
     {
-      "id": "warehouse_chunks/Warehouse_240219_GoPro_7_GX070600_100_3_2",
-      "video": "warehouse_chunks/Warehouse_240219_GoPro_7_GX070600_100_3_2.mp4",
+      "id": "Warehouse_240219_GoPro_7_GX070600_100_3_2",
+      "video": "Warehouse_240219_GoPro_7_GX070600_100_3_2.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are all workers wearing PPE (hardhats and safety vests)?"
     },
     {
-      "id": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_500_2_3",
-      "video": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_500_2_3.mp4",
+      "id": "Warehouse_240219_GoPro_7_GX010600_500_2_3",
+      "video": "Warehouse_240219_GoPro_7_GX010600_500_2_3.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the path obstructed for the forklift to pass?"
     },
     {
-      "id": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_500_1_4",
-      "video": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_500_1_4.mp4",
+      "id": "Warehouse_240219_GoPro_7_GX010600_500_1_4",
+      "video": "Warehouse_240219_GoPro_7_GX010600_500_1_4.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are the boxes properly stacked on the pallet loaded on the forklift?"
     },
     {
-      "id": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_400_1_5",
-      "video": "warehouse_chunks/Warehouse_240219_GoPro_7_GX010600_400_1_5.mp4",
+      "id": "Warehouse_240219_GoPro_7_GX010600_400_1_5",
+      "video": "Warehouse_240219_GoPro_7_GX010600_400_1_5.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the path obstructed for the forklift to pass?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_600_4_6",
-      "video": "warehouse_chunks/warehouse_1_600_4_6.mp4",
+      "id": "warehouse_1_600_4_6",
+      "video": "warehouse_1_600_4_6.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Did anyone experience a fall or end up on the ground?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_540_7",
-      "video": "warehouse_chunks/warehouse_1_540_7.mp4",
+      "id": "warehouse_1_540_7",
+      "video": "warehouse_1_540_7.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is any person near or in close proximity to the box when it falls?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_540_4_8",
-      "video": "warehouse_chunks/warehouse_1_540_4_8.mp4",
+      "id": "warehouse_1_540_4_8",
+      "video": "warehouse_1_540_4_8.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the operator or a person using a cell phone while working?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_425_6_9",
-      "video": "warehouse_chunks/warehouse_1_425_6_9.mp4",
+      "id": "warehouse_1_425_6_9",
+      "video": "warehouse_1_425_6_9.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the operator or a person jumping from the ladder?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_0_0_10",
-      "video": "warehouse_chunks/concat_wh_52_0_0_10.mp4",
+      "id": "concat_wh_52_0_0_10",
+      "video": "concat_wh_52_0_0_10.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does any box fall off the robot?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_425_4_11",
-      "video": "warehouse_chunks/warehouse_1_425_4_11.mp4",
+      "id": "warehouse_1_425_4_11",
+      "video": "warehouse_1_425_4_11.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are the boxes properly stacked as the operator lifts?"
     },
     {
-      "id": "warehouse_chunks/warehouse_1_120_12",
-      "video": "warehouse_chunks/warehouse_1_120_12.mp4",
+      "id": "warehouse_1_120_12",
+      "video": "warehouse_1_120_12.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does the operator throw any boxes?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_0_5_13",
-      "video": "warehouse_chunks/concat_wh_52_0_5_13.mp4",
+      "id": "concat_wh_52_0_5_13",
+      "video": "concat_wh_52_0_5_13.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does a box fall off the robot?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_0_14",
-      "video": "warehouse_chunks/concat_wh_52_300_0_14.mp4",
+      "id": "concat_wh_52_300_0_14",
+      "video": "concat_wh_52_300_0_14.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does anyone walk in front of the forklift?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_1_15",
-      "video": "warehouse_chunks/concat_wh_52_300_1_15.mp4",
+      "id": "concat_wh_52_300_1_15",
+      "video": "concat_wh_52_300_1_15.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Does anyone walk in front of the forklift?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_2_16",
-      "video": "warehouse_chunks/concat_wh_52_300_2_16.mp4",
+      "id": "concat_wh_52_300_2_16",
+      "video": "concat_wh_52_300_2_16.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is the path of the forklift clear?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_2_17",
-      "video": "warehouse_chunks/concat_wh_52_300_2_17.mp4",
+      "id": "concat_wh_52_300_2_17",
+      "video": "concat_wh_52_300_2_17.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are the boxes properly stacked on the pallet that is loaded on the forklift?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_1_18",
-      "video": "warehouse_chunks/concat_wh_52_300_1_18.mp4",
+      "id": "concat_wh_52_300_1_18",
+      "video": "concat_wh_52_300_1_18.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are all workers wearing PPE?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_300_3_19",
-      "video": "warehouse_chunks/concat_wh_52_300_3_19.mp4",
+      "id": "concat_wh_52_300_3_19",
+      "video": "concat_wh_52_300_3_19.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are the boxes properly stacked on the pallet that is loaded on the forklift?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_0_20",
-      "video": "warehouse_chunks/concat_wh_52_1890_0_20.mp4",
+      "id": "concat_wh_52_1890_0_20",
+      "video": "concat_wh_52_1890_0_20.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are all workers wearing PPE?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_4_21",
-      "video": "warehouse_chunks/concat_wh_52_1890_4_21.mp4",
+      "id": "concat_wh_52_1890_4_21",
+      "video": "concat_wh_52_1890_4_21.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are any boxes crushed?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_4_22",
-      "video": "warehouse_chunks/concat_wh_52_1890_4_22.mp4",
+      "id": "concat_wh_52_1890_4_22",
+      "video": "concat_wh_52_1890_4_22.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Do any boxes get dropped?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_5_23",
-      "video": "warehouse_chunks/concat_wh_52_1890_5_23.mp4",
+      "id": "concat_wh_52_1890_5_23",
+      "video": "concat_wh_52_1890_5_23.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Are any boxes crushed?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_5_24",
-      "video": "warehouse_chunks/concat_wh_52_1890_5_24.mp4",
+      "id": "concat_wh_52_1890_5_24",
+      "video": "concat_wh_52_1890_5_24.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Do any boxes get dropped?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_1890_9_25",
-      "video": "warehouse_chunks/concat_wh_52_1890_9_25.mp4",
+      "id": "concat_wh_52_1890_9_25",
+      "video": "concat_wh_52_1890_9_25.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is everyone wearing a hardhat and safety vest?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_2925_1_26",
-      "video": "warehouse_chunks/concat_wh_52_2925_1_26.mp4",
+      "id": "concat_wh_52_2925_1_26",
+      "video": "concat_wh_52_2925_1_26.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Do any boxes get dropped?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_2925_27",
-      "video": "warehouse_chunks/concat_wh_52_2925_27.mp4",
+      "id": "concat_wh_52_2925_27",
+      "video": "concat_wh_52_2925_27.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is anything blocking the path of the small yellow robot?"
     },
     {
-      "id": "warehouse_chunks/concat_wh_52_2925_28",
-      "video": "warehouse_chunks/concat_wh_52_2925_28.mp4",
+      "id": "concat_wh_52_2925_28",
+      "video": "concat_wh_52_2925_28.mp4",
       "system_prompt": "You are a warehouse monitoring system analyzing video footage. Your task is to answer safety and compliance questions strictly with \"Yes\" or \"No\".\nThe clip may not show the entire event, so rely on visible evidence. Infer from post-event evidence: \n- PPE compliance (hardhats, safety vests, etc.).\n- Path clear or obstructed for forklifts or robots.\n- Boxes stacked properly on pallets or being lifted.\n- Boxes crushed, dropped, or falling off forklifts/robots/operators.\n- Operator behavior (falling, using cell phone, throwing boxes).\n- Human safety risks (walking in front of forklift, near falling boxes, jumping from ladders).\n\nConfirm \"Yes\" only when visual evidence is clear.\nOtherwise, answer \"No\".",
       "question": "Is anything blocking the path of the forklift?"
     }

data/event_verification/{filtered/tailgating/location_a/test_annotation.json → data_jsons/annotations/tailgating_location_a.json}

@@ -1,170 +1,170 @@
 {
   "bcq": [
     {
-      "id": "videos/site_1/category_tailgate/10_15_2025_sp_8_35_08_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_15_2025_sp_8_35_08_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_15_2025_sp_8_35_08_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_15_2025_sp_8_35_08_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_20_2025_sp_4_13_08_sp_PM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_20_2025_sp_4_13_08_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_20_2025_sp_4_13_08_sp_PM_sp__lp_UTC-08_00_rp_",
+      "video": "11_20_2025_sp_4_13_08_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_24_2025_sp_9_44_18_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_24_2025_sp_9_44_18_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_24_2025_sp_9_44_18_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_24_2025_sp_9_44_18_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_20_2025_sp_1_01_55_sp_PM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_20_2025_sp_1_01_55_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_20_2025_sp_1_01_55_sp_PM_sp__lp_UTC-08_00_rp_",
+      "video": "11_20_2025_sp_1_01_55_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_30_25_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_30_25_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_30_25_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_30_25_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_15_2025_sp_8_38_19_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_15_2025_sp_8_38_19_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_15_2025_sp_8_38_19_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_15_2025_sp_8_38_19_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_8_2025_sp_8_38_03_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_8_2025_sp_8_38_03_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_8_2025_sp_8_38_03_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_8_2025_sp_8_38_03_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_09_05_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_09_05_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_09_05_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_09_05_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_46_58_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_46_58_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_46_58_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_46_58_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_24_2025_sp_10_23_17_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_24_2025_sp_10_23_17_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_24_2025_sp_10_23_17_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_24_2025_sp_10_23_17_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_9_2025_sp_8_48_30_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_9_2025_sp_8_48_30_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_9_2025_sp_8_48_30_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_9_2025_sp_8_48_30_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_8_2025_sp_8_43_54_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_8_2025_sp_8_43_54_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_8_2025_sp_8_43_54_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_8_2025_sp_8_43_54_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/11_21_2025_sp_11_56_03_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_tailgate/11_21_2025_sp_11_56_03_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_21_2025_sp_11_56_03_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_21_2025_sp_11_56_03_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_16_2025_sp_9_00_13_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_16_2025_sp_9_00_13_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_16_2025_sp_9_00_13_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_16_2025_sp_9_00_13_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_48_55_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_48_55_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_48_55_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_48_55_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_12_31_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_12_31_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_12_31_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_12_31_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_16_2025_sp_9_10_29_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_16_2025_sp_9_10_29_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_16_2025_sp_9_10_29_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_16_2025_sp_9_10_29_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_15_2025_sp_8_39_16_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_15_2025_sp_8_39_16_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_15_2025_sp_8_39_16_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_15_2025_sp_8_39_16_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_24_2025_sp_10_44_28_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_24_2025_sp_10_44_28_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_24_2025_sp_10_44_28_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_24_2025_sp_10_44_28_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_24_2025_sp_1_28_55_sp_PM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_24_2025_sp_1_28_55_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_24_2025_sp_1_28_55_sp_PM_sp__lp_UTC-08_00_rp_",
+      "video": "11_24_2025_sp_1_28_55_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_32_48_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_32_48_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_32_48_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_32_48_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_21_2025_sp_11_40_45_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_21_2025_sp_11_40_45_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_21_2025_sp_11_40_45_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_21_2025_sp_11_40_45_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_15_08_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_15_08_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_15_08_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_15_08_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_25_2025_sp_6_22_57_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_25_2025_sp_6_22_57_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_25_2025_sp_6_22_57_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_25_2025_sp_6_22_57_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/11_21_2025_sp_11_55_17_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_tailgate/11_21_2025_sp_11_55_17_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_21_2025_sp_11_55_17_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_21_2025_sp_11_55_17_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_tailgate/10_9_2025_sp_8_51_57_sp_PM_sp__lp_UTC-07_00_rp_",
-      "video": "videos/site_1/category_tailgate/10_9_2025_sp_8_51_57_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
+      "id": "10_9_2025_sp_8_51_57_sp_PM_sp__lp_UTC-07_00_rp_",
+      "video": "10_9_2025_sp_8_51_57_sp_PM_sp__lp_UTC-07_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_21_2025_sp_11_18_34_sp_AM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_21_2025_sp_11_18_34_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_21_2025_sp_11_18_34_sp_AM_sp__lp_UTC-08_00_rp_",
+      "video": "11_21_2025_sp_11_18_34_sp_AM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/site_1/category_badge/11_24_2025_sp_2_57_33_sp_PM_sp__lp_UTC-08_00_rp_",
-      "video": "videos/site_1/category_badge/11_24_2025_sp_2_57_33_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
+      "id": "11_24_2025_sp_2_57_33_sp_PM_sp__lp_UTC-08_00_rp_",
+      "video": "11_24_2025_sp_2_57_33_sp_PM_sp__lp_UTC-08_00_rp_.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     }

data/event_verification/{filtered/tailgating/location_b/test_annotation.json → data_jsons/annotations/tailgating_location_b.json}

@@ -1,134 +1,134 @@
 {
   "bcq": [
     {
-      "id": "videos/redacted/evs_6a52f11dad",
-      "video": "videos/redacted/evs_6a52f11dad.mp4",
+      "id": "evs_6a52f11dad",
+      "video": "evs_6a52f11dad.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_b561420691",
-      "video": "videos/redacted/evs_b561420691.mp4",
+      "id": "evs_b561420691",
+      "video": "evs_b561420691.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_907fe737cf",
-      "video": "videos/redacted/evs_907fe737cf.mp4",
+      "id": "evs_907fe737cf",
+      "video": "evs_907fe737cf.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_0ea91247d8",
-      "video": "videos/redacted/evs_0ea91247d8.mp4",
+      "id": "evs_0ea91247d8",
+      "video": "evs_0ea91247d8.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_6ad1a891ad",
-      "video": "videos/redacted/evs_6ad1a891ad.mp4",
+      "id": "evs_6ad1a891ad",
+      "video": "evs_6ad1a891ad.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_d0e459f682",
-      "video": "videos/redacted/evs_d0e459f682.mp4",
+      "id": "evs_d0e459f682",
+      "video": "evs_d0e459f682.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_2e30648c0a",
-      "video": "videos/redacted/evs_2e30648c0a.mp4",
+      "id": "evs_2e30648c0a",
+      "video": "evs_2e30648c0a.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_292daa255e",
-      "video": "videos/redacted/evs_292daa255e.mp4",
+      "id": "evs_292daa255e",
+      "video": "evs_292daa255e.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_a9e180fff3",
-      "video": "videos/redacted/evs_a9e180fff3.mp4",
+      "id": "evs_a9e180fff3",
+      "video": "evs_a9e180fff3.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_53f64ccbe8",
-      "video": "videos/redacted/evs_53f64ccbe8.mp4",
+      "id": "evs_53f64ccbe8",
+      "video": "evs_53f64ccbe8.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_b982d3f339",
-      "video": "videos/redacted/evs_b982d3f339.mp4",
+      "id": "evs_b982d3f339",
+      "video": "evs_b982d3f339.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_03018e0ecf",
-      "video": "videos/redacted/evs_03018e0ecf.mp4",
+      "id": "evs_03018e0ecf",
+      "video": "evs_03018e0ecf.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_bf746e9608",
-      "video": "videos/redacted/evs_bf746e9608.mp4",
+      "id": "evs_bf746e9608",
+      "video": "evs_bf746e9608.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_6e738337bc",
-      "video": "videos/redacted/evs_6e738337bc.mp4",
+      "id": "evs_6e738337bc",
+      "video": "evs_6e738337bc.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_f979eb0318",
-      "video": "videos/redacted/evs_f979eb0318.mp4",
+      "id": "evs_f979eb0318",
+      "video": "evs_f979eb0318.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_024ae78480",
-      "video": "videos/redacted/evs_024ae78480.mp4",
+      "id": "evs_024ae78480",
+      "video": "evs_024ae78480.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_fa68a5a4f8",
-      "video": "videos/redacted/evs_fa68a5a4f8.mp4",
+      "id": "evs_fa68a5a4f8",
+      "video": "evs_fa68a5a4f8.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_eed8192951",
-      "video": "videos/redacted/evs_eed8192951.mp4",
+      "id": "evs_eed8192951",
+      "video": "evs_eed8192951.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_32231b0bd6",
-      "video": "videos/redacted/evs_32231b0bd6.mp4",
+      "id": "evs_32231b0bd6",
+      "video": "evs_32231b0bd6.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_a713802c9d",
-      "video": "videos/redacted/evs_a713802c9d.mp4",
+      "id": "evs_a713802c9d",
+      "video": "evs_a713802c9d.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_3f674e8c19",
-      "video": "videos/redacted/evs_3f674e8c19.mp4",
+      "id": "evs_3f674e8c19",
+      "video": "evs_3f674e8c19.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     },
     {
-      "id": "videos/redacted/evs_6a4da56832",
-      "video": "videos/redacted/evs_6a4da56832.mp4",
+      "id": "evs_6a4da56832",
+      "video": "evs_6a4da56832.mp4",
       "system_prompt": "You are an expert AI assistant for video analysis. Your task is to accurately classify whether a surveillance video depicts **normal access** or **tailgating** behavior, based on the strict definitions below.\n\n# Category Definitions\n\n- **Normal Access**:  \nA person (or group) enters a secure area **properly authenticated** (e.g., by using a badge, keycard, or biometric system). Only those with authorization enter. There is **no evidence of security breach** or abnormal entry.  \n\n- **Tailgating**:  \nOne or more individuals **enter a secure area without authorization** by following closely behind an authorized person who has legitimately gained access. The unauthorized individual does not use valid credentials but takes advantage of the door being open. This includes:  \n- Following immediately behind someone with a badge swipe.  \n- Entering as part of a group where only the first person authenticates.  \n- Entering without any visible authentication while leveraging someone else's access.",
       "question": "Does the video depict tailgating behavior? Answer \"Yes\" or \"No\"."
     }

data/event_verification/{filtered/warehouse_near_miss/test_annotations.json → data_jsons/annotations/warehouse_near_miss.json}

@@ -1,280 +1,280 @@
 {
   "bcq": [
     {
-      "id": "positive/scene_07_01_00-23-52_to_00-25-33_GoPro1_Fork_Lift_stopped_while_person_crossing_the_isle_08-22",
-      "video": "positive/scene_07_01_00-23-52_to_00-25-33_GoPro1_Fork_Lift_stopped_while_person_crossing_the_isle_08-22.mp4",
+      "id": "scene_07_01_00-23-52_to_00-25-33_GoPro1_Fork_Lift_stopped_while_person_crossing_the_isle_08-22",
+      "video": "scene_07_01_00-23-52_to_00-25-33_GoPro1_Fork_Lift_stopped_while_person_crossing_the_isle_08-22.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_08_01_00-00-46_to_00-02-20_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_01-15",
-      "video": "positive/scene_08_01_00-00-46_to_00-02-20_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_01-15.mp4",
+      "id": "scene_08_01_00-00-46_to_00-02-20_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_01-15",
+      "video": "scene_08_01_00-00-46_to_00-02-20_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_01-15.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_08_02_00-02-20_to_00-04-56_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_08-22",
-      "video": "positive/scene_08_02_00-02-20_to_00-04-56_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_08-22.mp4",
+      "id": "scene_08_02_00-02-20_to_00-04-56_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_08-22",
+      "video": "scene_08_02_00-02-20_to_00-04-56_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_08-22.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_08_03_00-04-56_to_00-08-15_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_04-18",
-      "video": "positive/scene_08_03_00-04-56_to_00-08-15_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_04-18.mp4",
+      "id": "scene_08_03_00-04-56_to_00-08-15_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_04-18",
+      "video": "scene_08_03_00-04-56_to_00-08-15_GoPro1_Fork_Lift_crossing_while_person_running_in_front_of_it_04-18.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_09_01_00-08-15_to_00-10-22_GoPro1_Fork_Lift_moving_while_person_on_the_phone_crossing_the_isle_06-20",
-      "video": "positive/scene_09_01_00-08-15_to_00-10-22_GoPro1_Fork_Lift_moving_while_person_on_the_phone_crossing_the_isle_06-20.mp4",
+      "id": "scene_09_01_00-08-15_to_00-10-22_GoPro1_Fork_Lift_moving_while_person_on_the_phone_crossing_the_isle_06-20",
+      "video": "scene_09_01_00-08-15_to_00-10-22_GoPro1_Fork_Lift_moving_while_person_on_the_phone_crossing_the_isle_06-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_10_01_00-10-22_to_00-13-12_GoPro1_Fork_Lift_moving_while_person_crossing_the_isle_06-20",
-      "video": "positive/scene_10_01_00-10-22_to_00-13-12_GoPro1_Fork_Lift_moving_while_person_crossing_the_isle_06-20.mp4",
+      "id": "scene_10_01_00-10-22_to_00-13-12_GoPro1_Fork_Lift_moving_while_person_crossing_the_isle_06-20",
+      "video": "scene_10_01_00-10-22_to_00-13-12_GoPro1_Fork_Lift_moving_while_person_crossing_the_isle_06-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_11_01_00-13-12_to_00-16-16_GoPro1_Fork_Lift_moving_while_multiple_people_in_the_scene_04-22",
-      "video": "positive/scene_11_01_00-13-12_to_00-16-16_GoPro1_Fork_Lift_moving_while_multiple_people_in_the_scene_04-22.mp4",
+      "id": "scene_11_01_00-13-12_to_00-16-16_GoPro1_Fork_Lift_moving_while_multiple_people_in_the_scene_04-22",
+      "video": "scene_11_01_00-13-12_to_00-16-16_GoPro1_Fork_Lift_moving_while_multiple_people_in_the_scene_04-22.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_12_01_00-16-16_to_00-17-31_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_06-20",
-      "video": "positive/scene_12_01_00-16-16_to_00-17-31_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_06-20.mp4",
+      "id": "scene_12_01_00-16-16_to_00-17-31_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_06-20",
+      "video": "scene_12_01_00-16-16_to_00-17-31_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_06-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_12_02_00-17-31_to_00-19-50_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_02-16",
-      "video": "positive/scene_12_02_00-17-31_to_00-19-50_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_02-16.mp4",
+      "id": "scene_12_02_00-17-31_to_00-19-50_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_02-16",
+      "video": "scene_12_02_00-17-31_to_00-19-50_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_02-16.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_14_01_00-19-50_to_00-22-54_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_04-18",
-      "video": "positive/scene_14_01_00-19-50_to_00-22-54_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_04-18.mp4",
+      "id": "scene_14_01_00-19-50_to_00-22-54_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_04-18",
+      "video": "scene_14_01_00-19-50_to_00-22-54_GoPro1_Fork_Lift_moving_while_person_walking_behind_the_forklift_04-18.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_16_01_00-22-54_to_00-25-38_GoPro1_person_walking_in_front_of_fork_lift_04-48",
-      "video": "positive/scene_16_01_00-22-54_to_00-25-38_GoPro1_person_walking_in_front_of_fork_lift_04-48.mp4",
+      "id": "scene_16_01_00-22-54_to_00-25-38_GoPro1_person_walking_in_front_of_fork_lift_04-48",
+      "video": "scene_16_01_00-22-54_to_00-25-38_GoPro1_person_walking_in_front_of_fork_lift_04-48.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_17_01_00-25-38_to_00-27-32_GoPro1_person_running_in_front_of_fork_lift_02-16",
-      "video": "positive/scene_17_01_00-25-38_to_00-27-32_GoPro1_person_running_in_front_of_fork_lift_02-16.mp4",
+      "id": "scene_17_01_00-25-38_to_00-27-32_GoPro1_person_running_in_front_of_fork_lift_02-16",
+      "video": "scene_17_01_00-25-38_to_00-27-32_GoPro1_person_running_in_front_of_fork_lift_02-16.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_17_02_00-27-32_to_00-30-55_GoPro1_person_running_in_front_of_fork_lift_02-26",
-      "video": "positive/scene_17_02_00-27-32_to_00-30-55_GoPro1_person_running_in_front_of_fork_lift_02-26.mp4",
+      "id": "scene_17_02_00-27-32_to_00-30-55_GoPro1_person_running_in_front_of_fork_lift_02-26",
+      "video": "scene_17_02_00-27-32_to_00-30-55_GoPro1_person_running_in_front_of_fork_lift_02-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_18_01_00-30-55_to_00-33-57_GoPro1_person_jumping_to_not_get_hit_by_the_forklift_00-20",
-      "video": "positive/scene_18_01_00-30-55_to_00-33-57_GoPro1_person_jumping_to_not_get_hit_by_the_forklift_00-20.mp4",
+      "id": "scene_18_01_00-30-55_to_00-33-57_GoPro1_person_jumping_to_not_get_hit_by_the_forklift_00-20",
+      "video": "scene_18_01_00-30-55_to_00-33-57_GoPro1_person_jumping_to_not_get_hit_by_the_forklift_00-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_19_01_00-33-57_to_00-35-41_GoPro1_fork_lift_moving_backwards_person_cutting_in_front_of_the_fo_04-24",
-      "video": "positive/scene_19_01_00-33-57_to_00-35-41_GoPro1_fork_lift_moving_backwards_person_cutting_in_front_of_the_fo_04-24.mp4",
+      "id": "scene_19_01_00-33-57_to_00-35-41_GoPro1_fork_lift_moving_backwards_person_cutting_in_front_of_the_fo_04-24",
+      "video": "scene_19_01_00-33-57_to_00-35-41_GoPro1_fork_lift_moving_backwards_person_cutting_in_front_of_the_fo_04-24.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_20_01_00-35-41_to_00-37-23_GoPro1_fork_lift_going_backwards_person_running_passed_04-22",
-      "video": "positive/scene_20_01_00-35-41_to_00-37-23_GoPro1_fork_lift_going_backwards_person_running_passed_04-22.mp4",
+      "id": "scene_20_01_00-35-41_to_00-37-23_GoPro1_fork_lift_going_backwards_person_running_passed_04-22",
+      "video": "scene_20_01_00-35-41_to_00-37-23_GoPro1_fork_lift_going_backwards_person_running_passed_04-22.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_21_01_00-37-23_to_00-39-30_GoPro1_fork_lift_going_backwards_person_stops_06-24",
-      "video": "positive/scene_21_01_00-37-23_to_00-39-30_GoPro1_fork_lift_going_backwards_person_stops_06-24.mp4",
+      "id": "scene_21_01_00-37-23_to_00-39-30_GoPro1_fork_lift_going_backwards_person_stops_06-24",
+      "video": "scene_21_01_00-37-23_to_00-39-30_GoPro1_fork_lift_going_backwards_person_stops_06-24.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_22_01_00-39-30_to_00-45-36_GoPro1_fork_lift_moving_person_hesitating_and_stepping_back_01-20",
-      "video": "positive/scene_22_01_00-39-30_to_00-45-36_GoPro1_fork_lift_moving_person_hesitating_and_stepping_back_01-20.mp4",
+      "id": "scene_22_01_00-39-30_to_00-45-36_GoPro1_fork_lift_moving_person_hesitating_and_stepping_back_01-20",
+      "video": "scene_22_01_00-39-30_to_00-45-36_GoPro1_fork_lift_moving_person_hesitating_and_stepping_back_01-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_23_01_00-45-36_to_00-49-03_GoPro1_boxes_blocking_the_view_of_the_driver_and_person_crossing_06-26",
-      "video": "positive/scene_23_01_00-45-36_to_00-49-03_GoPro1_boxes_blocking_the_view_of_the_driver_and_person_crossing_06-26.mp4",
+      "id": "scene_23_01_00-45-36_to_00-49-03_GoPro1_boxes_blocking_the_view_of_the_driver_and_person_crossing_06-26",
+      "video": "scene_23_01_00-45-36_to_00-49-03_GoPro1_boxes_blocking_the_view_of_the_driver_and_person_crossing_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_25_01_00-02-02_to_00-05-05_GoPro1_person_working_on_boxes_while_fork_lift_approaches_06-30",
-      "video": "positive/scene_25_01_00-02-02_to_00-05-05_GoPro1_person_working_on_boxes_while_fork_lift_approaches_06-30.mp4",
+      "id": "scene_25_01_00-02-02_to_00-05-05_GoPro1_person_working_on_boxes_while_fork_lift_approaches_06-30",
+      "video": "scene_25_01_00-02-02_to_00-05-05_GoPro1_person_working_on_boxes_while_fork_lift_approaches_06-30.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_26_01_00-05-05_to_00-08-50_GoPro1_same_as_above_person_jumping_05-24",
-      "video": "positive/scene_26_01_00-05-05_to_00-08-50_GoPro1_same_as_above_person_jumping_05-24.mp4",
+      "id": "scene_26_01_00-05-05_to_00-08-50_GoPro1_same_as_above_person_jumping_05-24",
+      "video": "scene_26_01_00-05-05_to_00-08-50_GoPro1_same_as_above_person_jumping_05-24.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "positive/scene_27_01_00-08-50_to_00-15-25_GoPro1_person_bending_down_fork_lift_moving_forward_10-30",
-      "video": "positive/scene_27_01_00-08-50_to_00-15-25_GoPro1_person_bending_down_fork_lift_moving_forward_10-30.mp4",
+      "id": "scene_27_01_00-08-50_to_00-15-25_GoPro1_person_bending_down_fork_lift_moving_forward_10-30",
+      "video": "scene_27_01_00-08-50_to_00-15-25_GoPro1_person_bending_down_fork_lift_moving_forward_10-30.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T1_C2_CS_S13T1_1-12-11-59_chunk_5__event_005_5",
-      "video": "negative/Scene_13_S13T1_C2_CS_S13T1_1-12-11-59_chunk_5__event_005_5.mp4",
+      "id": "Scene_13_S13T1_C2_CS_S13T1_1-12-11-59_chunk_5__event_005_5",
+      "video": "Scene_13_S13T1_C2_CS_S13T1_1-12-11-59_chunk_5__event_005_5.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T3_C5_AS_S13T3_01-18-12-10_chunk_2__event_001_1",
-      "video": "negative/Scene_13_S13T3_C5_AS_S13T3_01-18-12-10_chunk_2__event_001_1.mp4",
+      "id": "Scene_13_S13T3_C5_AS_S13T3_01-18-12-10_chunk_2__event_001_1",
+      "video": "Scene_13_S13T3_C5_AS_S13T3_01-18-12-10_chunk_2__event_001_1.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_5__event_008_8",
-      "video": "negative/Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_5__event_008_8.mp4",
+      "id": "Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_5__event_008_8",
+      "video": "Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_5__event_008_8.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_6__event_001_1",
-      "video": "negative/Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_6__event_001_1.mp4",
+      "id": "Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_6__event_001_1",
+      "video": "Scene_13_S13T4_C4_AS_S13T4_1-12-12-28_chunk_6__event_001_1.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C5_AS_S13T4_00-58-12-14_chunk_5__event_004_4",
-      "video": "negative/Scene_13_S13T4_C5_AS_S13T4_00-58-12-14_chunk_5__event_004_4.mp4",
+      "id": "Scene_13_S13T4_C5_AS_S13T4_00-58-12-14_chunk_5__event_004_4",
+      "video": "Scene_13_S13T4_C5_AS_S13T4_00-58-12-14_chunk_5__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_1__event_004_4",
-      "video": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_1__event_004_4.mp4",
+      "id": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_1__event_004_4",
+      "video": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_1__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_5__event_004_4",
-      "video": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_5__event_004_4.mp4",
+      "id": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_5__event_004_4",
+      "video": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_5__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_6__event_001_1",
-      "video": "negative/Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_6__event_001_1.mp4",
+      "id": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_6__event_001_1",
+      "video": "Scene_13_S13T4_C6_AS_S13T4_00-43-11-59_chunk_6__event_001_1.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T5_C2_AS_S13T5_0-51-11-39_chunk_5__event_004_4",
-      "video": "negative/Scene_13_S13T5_C2_AS_S13T5_0-51-11-39_chunk_5__event_004_4.mp4",
+      "id": "Scene_13_S13T5_C2_AS_S13T5_0-51-11-39_chunk_5__event_004_4",
+      "video": "Scene_13_S13T5_C2_AS_S13T5_0-51-11-39_chunk_5__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T5_C3_AS_S13T5_0-53-11-38_chunk_5__event_004_4",
-      "video": "negative/Scene_13_S13T5_C3_AS_S13T5_0-53-11-38_chunk_5__event_004_4.mp4",
+      "id": "Scene_13_S13T5_C3_AS_S13T5_0-53-11-38_chunk_5__event_004_4",
+      "video": "Scene_13_S13T5_C3_AS_S13T5_0-53-11-38_chunk_5__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T5_C4_AS_S13T5_0-53-11-39_chunk_5__event_004_4",
-      "video": "negative/Scene_13_S13T5_C4_AS_S13T5_0-53-11-39_chunk_5__event_004_4.mp4",
+      "id": "Scene_13_S13T5_C4_AS_S13T5_0-53-11-39_chunk_5__event_004_4",
+      "video": "Scene_13_S13T5_C4_AS_S13T5_0-53-11-39_chunk_5__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_13_S13T5_C6_AS_S13T5_00-29-11-15_chunk_5__event_003_3",
-      "video": "negative/Scene_13_S13T5_C6_AS_S13T5_00-29-11-15_chunk_5__event_003_3.mp4",
+      "id": "Scene_13_S13T5_C6_AS_S13T5_00-29-11-15_chunk_5__event_003_3",
+      "video": "Scene_13_S13T5_C6_AS_S13T5_00-29-11-15_chunk_5__event_003_3.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_4_S4T4_C2_CV_S4T4_00-54-10-48_chunk_5__event_001_1",
-      "video": "negative/Scene_4_S4T4_C2_CV_S4T4_00-54-10-48_chunk_5__event_001_1.mp4",
+      "id": "Scene_4_S4T4_C2_CV_S4T4_00-54-10-48_chunk_5__event_001_1",
+      "video": "Scene_4_S4T4_C2_CV_S4T4_00-54-10-48_chunk_5__event_001_1.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_4_S4T4_C4_CS_S4T4_00-54-10-48_chunk_4__event_003_3",
-      "video": "negative/Scene_4_S4T4_C4_CS_S4T4_00-54-10-48_chunk_4__event_003_3.mp4",
+      "id": "Scene_4_S4T4_C4_CS_S4T4_00-54-10-48_chunk_4__event_003_3",
+      "video": "Scene_4_S4T4_C4_CS_S4T4_00-54-10-48_chunk_4__event_003_3.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_1__event_004_4",
-      "video": "negative/Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_1__event_004_4.mp4",
+      "id": "Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_1__event_004_4",
+      "video": "Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_1__event_004_4.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_5__event_002_2",
-      "video": "negative/Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_5__event_002_2.mp4",
+      "id": "Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_5__event_002_2",
+      "video": "Scene_4_S4T4_C6_CS_S4T4_00-54-10-48_chunk_5__event_002_2.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_01_01_00-00-00_to_00-07-34_GoPro1_Calibration_with_people_walking_around_06-26",
-      "video": "negative/scene_01_01_00-00-00_to_00-07-34_GoPro1_Calibration_with_people_walking_around_06-26.mp4",
+      "id": "scene_01_01_00-00-00_to_00-07-34_GoPro1_Calibration_with_people_walking_around_06-26",
+      "video": "scene_01_01_00-00-00_to_00-07-34_GoPro1_Calibration_with_people_walking_around_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_02_01_00-07-34_to_00-11-38_GoPro1_Forklifts_being_moved_out_of_the_way_06-26",
-      "video": "negative/scene_02_01_00-07-34_to_00-11-38_GoPro1_Forklifts_being_moved_out_of_the_way_06-26.mp4",
+      "id": "scene_02_01_00-07-34_to_00-11-38_GoPro1_Forklifts_being_moved_out_of_the_way_06-26",
+      "video": "scene_02_01_00-07-34_to_00-11-38_GoPro1_Forklifts_being_moved_out_of_the_way_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_04_01_00-11-38_to_00-19-46_GoPro1_Forklift_entering_the_aisle_no_pedestrians_around_06-26",
-      "video": "negative/scene_04_01_00-11-38_to_00-19-46_GoPro1_Forklift_entering_the_aisle_no_pedestrians_around_06-26.mp4",
+      "id": "scene_04_01_00-11-38_to_00-19-46_GoPro1_Forklift_entering_the_aisle_no_pedestrians_around_06-26",
+      "video": "scene_04_01_00-11-38_to_00-19-46_GoPro1_Forklift_entering_the_aisle_no_pedestrians_around_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_05_01_00-19-46_to_00-21-03_GoPro1_Fork_Lift_crossing_people_crossing_afterwards_06-26",
-      "video": "negative/scene_05_01_00-19-46_to_00-21-03_GoPro1_Fork_Lift_crossing_people_crossing_afterwards_06-26.mp4",
+      "id": "scene_05_01_00-19-46_to_00-21-03_GoPro1_Fork_Lift_crossing_people_crossing_afterwards_06-26",
+      "video": "scene_05_01_00-19-46_to_00-21-03_GoPro1_Fork_Lift_crossing_people_crossing_afterwards_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_06_01_00-21-03_to_00-23-52_GoPro1_Fork_Lift_crossing_people_following_the_forklift_06-26",
-      "video": "negative/scene_06_01_00-21-03_to_00-23-52_GoPro1_Fork_Lift_crossing_people_following_the_forklift_06-26.mp4",
+      "id": "scene_06_01_00-21-03_to_00-23-52_GoPro1_Fork_Lift_crossing_people_following_the_forklift_06-26",
+      "video": "scene_06_01_00-21-03_to_00-23-52_GoPro1_Fork_Lift_crossing_people_following_the_forklift_06-26.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_28_01_00-15-25_to_00-27-58_GoPro1_boxes_falling_04-22",
-      "video": "negative/scene_28_01_00-15-25_to_00-27-58_GoPro1_boxes_falling_04-22.mp4",
+      "id": "scene_28_01_00-15-25_to_00-27-58_GoPro1_boxes_falling_04-22",
+      "video": "scene_28_01_00-15-25_to_00-27-58_GoPro1_boxes_falling_04-22.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_29_01_00-01-07_to_00-10-18_GoPro1_driver_picks_up_trash_00-50",
-      "video": "negative/scene_29_01_00-01-07_to_00-10-18_GoPro1_driver_picks_up_trash_00-50.mp4",
+      "id": "scene_29_01_00-01-07_to_00-10-18_GoPro1_driver_picks_up_trash_00-50",
+      "video": "scene_29_01_00-01-07_to_00-10-18_GoPro1_driver_picks_up_trash_00-50.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     },
     {
-      "id": "negative/scene_29_01_00-09-27_to_00-12-53_GoPro1_driver_picks_up_trash_00-20",
-      "video": "negative/scene_29_01_00-09-27_to_00-12-53_GoPro1_driver_picks_up_trash_00-20.mp4",
+      "id": "scene_29_01_00-09-27_to_00-12-53_GoPro1_driver_picks_up_trash_00-20",
+      "video": "scene_29_01_00-09-27_to_00-12-53_GoPro1_driver_picks_up_trash_00-20.mp4",
       "system_prompt": "You are an industrial safety analyst reviewing warehouse video. Determine whether the clip depicts a near-miss collision between a person and a forklift (or other powered vehicle). Answer Yes or No.",
       "question": "Please tell whether the video contains near-miss collision between person and forklift. Your final answer should be either Yes or No."
     }
   ]
-}
+}