VANTAGE-Bench update: prompts + question-only annotations + Vantage2DPointing rename + test split + data/README + CHANGELOG

CHANGELOG.md

@@ -0,0 +1,28 @@
+# Changelog
+
+All notable changes to **`nvidia/PhysicalAI-VANTAGE-Bench-Subset`** on Hugging Face.
+
+## 2026-05-15
+
+- Per-task `prompt.json` added under `data/2dbbox/` and
+  `data/dense_captioning/` (schema: `{"prompt": "<text>"}`).
+- Question-only annotation JSONs added under
+  `data/vqa/data_jsons/annotations/`,
+  `data/temporal_localization/data_jsons/annotations/`,
+  `data/event_verification/filtered/**`,
+  and `data/referring/refdrone_test_llava.json`. Answer fields
+  (`gt`, `gt_option`, `answer`, GT bbox coordinates, etc.) are
+  stripped — only the question side ships.
+- `Metropolis2DPointing` references renamed to `Vantage2DPointing`.
+- New `data/README.md` summarizing the dataset layout and listing the
+  per-task prompts.
+
+## 2026-05-09
+- **`data/` restructured.** Top-level task directories renamed:
+  `dense_captioning/`, `event_verification/`, `pointing/`,
+  `referring/`, `temporal_localization/`, `vqa/`. The legacy
+  `Spatial/` directory was dropped.
+
+## 2026-05-04
+- **Initial release**: 4 GB sample uploaded to
+  `nvidia/PhysicalAI-VANTAGE-Bench-Subset` under `data/` (PR #1).

README.md

@@ -2,6 +2,10 @@
 license: other
 license_name: nvidia-evaluation-data-license
 license_link: LICENSE.md
+dataset_info:
+  splits:
+    - name: test
+      num_examples: 35027
 ---
 
 # VANTAGE-BENCH

data/2dbbox/prompt.json

@@ -0,0 +1,3 @@
+{
+  "prompt": "Locate every instance that belongs to the following categories: 'person'. For each instance of the class, report bbox coordinates in JSON format. Do not group instances and report only individual instances. Avoid reporting duplicate instances."
+}

data/README.md

@@ -0,0 +1,69 @@
+# VANTAGE-Bench — `data/`
+
+Brief overview of the dataset structure and per-task prompts.
+Ground-truth answers are held server-side; only the **question side** of
+each annotation ships here.
+
+## Layout
+
+```
+data/
+├── 2dbbox/                       # 2D bounding-box detection
+│   ├── prompt.json
+│   └── <sequence>/images/*.jpg
+├── dense_captioning/             # Dense video captioning
+│   ├── 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}
+├── pointing/                     # 2D spatial pointing
+│   └── Vantage2DPointing.tsv
+├── referring/                    # 2D referring expressions
+│   └── refdrone_test_llava.json
+├── temporal_localization/        # Temporal grounding
+│   ├── *.mp4
+│   └── data_jsons/annotations/*.json
+├── tracking/                     # Stateless single-object tracking
+│   └── sot_benchmark.jsonl
+└── vqa/                          # Video question answering
+    ├── *.mp4
+    └── data_jsons/annotations/*.json
+```
+
+## Per-task prompts
+
+Tasks without a per-entry `question` field carry a top-level
+`prompt.json` with the model instruction (schema: `{"prompt": "<text>"}`).
+
+### `2dbbox/` — 2D Detection
+> Locate every instance that belongs to the following categories: `person`. For each instance of the class, report bbox coordinates in JSON format. Do not group instances and report only individual instances. Avoid reporting duplicate instances.
+
+### `dense_captioning/` — Dense Video Captioning
+> Describe the notable events in the provided video. Provide the result in json format with `mm:ss.ff` format for time depiction for each event. Use keywords `start`, `end` and `caption` in the json output.
+
+### `vqa/` — Video Question Answering
+Per-entry questions in `vqa/data_jsons/annotations/*.json`. Each entry has `{q_uid, question, options, …}`; answer keys (`gt`, `gt_option`, `*_update_*`, etc.) are removed.
+
+### `temporal_localization/` — Temporal Grounding
+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.
+
+### `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.
+
+### `referring/` — 2D Referring Expressions
+`refdrone_test_llava.json` — list of LLaVA conversation entries. Only the `human` turn (the question) is retained; the `gpt` turn (predicted bboxes) and GT meta fields are removed.
+
+### `tracking/` — Stateless Single-Object Tracking
+`sot_benchmark.jsonl` — one JSON object per clip with `seq_id`, `scene`, `camera`, `init_bbox` (the seed bounding box you're given as input), `init_frame_id`, and `canonical_frame_ids` (the frames you must predict at). Ground-truth trajectories are held server-side.
+
+## Submitting predictions
+
+See the top-level `README.md` for the eval-server instructions per task.

data/dense_captioning/prompt.json

@@ -0,0 +1,3 @@
+{
+  "prompt": "Describe the notable events in the provided video. Provide the result in json format with 'mm:ss.ff' format for time depiction for each event. Use keywords 'start', 'end' and 'caption' in the json output."
+}

data/event_verification/filtered/metropolis_event_verification/test_annotation.json

@@ -0,0 +1,406 @@
+{
+  "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "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\".",
+      "question": "Did a collision occur between two or more vehicles?"
+    },
+    {
+      "id": "safety_chunks/evs_134db13b21",
+      "video": "safety_chunks/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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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

@@ -0,0 +1,172 @@
+{
+  "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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

@@ -0,0 +1,136 @@
+{
+  "bcq": [
+    {
+      "id": "videos/redacted/evs_6a52f11dad",
+      "video": "videos/redacted/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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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

@@ -0,0 +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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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",
+      "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."
+    }
+  ]
+}

data/temporal_localization/data_jsons/annotations/nv_lita_benchmark.json

@@ -0,0 +1,407 @@
+[
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_400",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_400.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"A man drives a forklift behind three workers\" take place? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_400",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_400.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"Three factory workers in green vests wearing yellow hats talk\" take place? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_400",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_400.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"The three workers move out of the way of the forklift\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_400",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_400.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"The forklift moves forward and rotates 90 degrees in front of a shelf of boxes\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_400",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_400.mp4_4",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"The forklift lifts its arm and inserts it into a shelf of boxes\" take place? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_500",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_500.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"A forklift's bars go underneath boxes on a shelf\" depicted in the video? Provide a response using only start and end timestamps.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_500",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_500.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"The forklift slowly takes the boxes off of the shelf\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "Warehouse_240219_GoPro_7_GX010600_500",
+    "question_id": "Warehouse_240219_GoPro_7_GX010600_500.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"The forklift drives into the distance\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.026633
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"A box falls\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The forklift waits for the robot in its way\" happen? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A worker walks to the box\" happen? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"A lady picks up the box\" happen in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_4",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The worker walks back\" happen? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_5",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The box falls again\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_6",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The lady picks up the box again\" happen? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_7",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"The forklift moves forward\" take place? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_0",
+    "question_id": "concat_wh_52_0.mp4_8",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The forklift's arms go up to pick up boxes\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_300",
+    "question_id": "concat_wh_52_300.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A forklift with boxes moves forward\" happen? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_300",
+    "question_id": "concat_wh_52_300.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"People cross in front of the forklift\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_300",
+    "question_id": "concat_wh_52_300.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The forklift moves forward\" happen? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_300",
+    "question_id": "concat_wh_52_300.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"The forklift's arms go up with boxes on top\" depicted in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"A forklift removes boxes from the shelf\" happen in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"People without uniforms are walking in the warehouse\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A forklift with boxes on it moves forward\" happen? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"There are boxes on the floor\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_4",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"The forklift is stuck because of boxes on the floor\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_5",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"People remove the boxes\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_910",
+    "question_id": "concat_wh_52_910.mp4_6",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"The forklift with boxes on it moves forward\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"A worker wearing a protective vest and yellow hard hat walks forward and smiles\" happen in the video? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A worker takes of his hat and puts it back on\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A cart with boxes on it arrives\" happen? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"Workers move boxes down a conveyor belt\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_4",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When is \"A box falls off the conveyor belt\" depicted in the video? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_5",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A box falls off the conveyor belt\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_6",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"A box falls off the conveyor belt\" take place? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_7",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"Workers are chitchatting\" happen? Provide a response using only start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_8",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A man in a white shirt without a uniform is holding his phone and walking\" happen? Convey your answer using start and end timestamps exclusively.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_1890",
+    "question_id": "concat_wh_52_1890.mp4_9",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"Two people wearing dark clothes and no uniform are walking and chatting\" happen? Answer the question only using start and end timestamps.",
+    "duration": 60.0
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_0",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A robot carrying a box is still in a warehouse, and there are people on the sides\" happen? Provide a response using only start and end timestamps.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_1",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"A box falls off the robot\" take place? Answer the question only using start and end timestamps.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_2",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A man wearing white without uniform walks closer to the camera\" happen? Provide a response using only start and end timestamps.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_3",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"A man puts the box back on the robot\" happen in the video? Convey your answer using start and end timestamps exclusively.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_4",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what time in the video does \"The man wearing white without uniform walks away\" take place? Answer the question only using start and end timestamps.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_5",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "At what point in the video does \"A forklift moves closer to the camera\" happen? Provide a response using only start and end timestamps.",
+    "duration": 59.562
+  },
+  {
+    "vid": "concat_wh_52_2925",
+    "question_id": "concat_wh_52_2925.mp4_6",
+    "industry": "",
+    "event_type": "",
+    "task_type": "",
+    "question": "When does \"A robot with a box is blocking the forklift\" happen in the video? Provide a response using only start and end timestamps.",
+    "duration": 59.562
+  }
+]

data/vqa/data_jsons/annotations/metrics_temporal_filtered_ss.json

@@ -0,0 +1,340 @@
+[
+  {
+    "q_uid": "GX010071_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "Which of the following is true according to the segment?",
+    "options": [
+      "everyone is holding something",
+      "some people may have empty hands",
+      "no one is carrying a laptop",
+      "only one person at a time can leave the room"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010071_Clip_6.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "In the scene, what caused the transparent gate to open?",
+    "options": [
+      "A man touching a metal part of the transparent gate",
+      "A man scanning a card beside the transparent gate",
+      "The door opens automatically as the person approaches",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010032_Clip_2.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "In the scene, what is causing the transparent gates to open?",
+    "options": [
+      "People scanning cards beside the transparent doors",
+      "People clicking a button beside the transparent doors",
+      "It senses a person approaching and opens automatically",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010014_Clip_1.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What is causing the transparent gates to open?",
+    "options": [
+      "People scanning cards beside the gates",
+      "People pushing a button beside the gates",
+      "When someone approaches, the gate automatically opens after detecting their presence",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010031_Clip_3.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "Why was the person wearing a black T-shirt stopped by others near the door?",
+    "options": [
+      "was for higher level",
+      "had a no-black shirts policy",
+      "privacy purpose",
+      "both a and c"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010029_Clip_6.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "Why did the door on the right close?",
+    "options": [
+      "A person pulling the door",
+      "A person pushing the door",
+      "A person rotating the door handle",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010030_Clip_2.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "In the scene, what is causing the turnstiles to open?",
+    "options": [
+      "People pushing a button beside the turnstile",
+      "People scanning cards beside the turnstile",
+      "When someone approaches the turnstile, it detects their presence and opens automatically",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010069_Clip_8.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the door to close?",
+    "options": [
+      "The door being closed automatically",
+      "A person closing the door",
+      "A person scanning a card beside the door",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010070_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What is the least likely reason the person stood alone, folding his hands, before others?",
+    "options": [
+      "had permission to exit early",
+      "finished the work early",
+      "skipped a meeting and reached early",
+      "a secret force pulled him ahead"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010069_Clip_5.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the door to close?",
+    "options": [
+      "closed automatically",
+      "a man pushing the door",
+      "a man pulling the door",
+      "none of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010012_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the transparent gate to open and close?",
+    "options": [
+      "People open and close it manually",
+      "The gate has sensors",
+      "There is a switch near the gate",
+      "The gate opens and closes randomly"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010030_Clip_1.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the transparent doors to open in the video segment?",
+    "options": [
+      "A vehicle passing through",
+      "A man scanning a card beside the transparent doors",
+      "Objects passing through",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010011_Clip_3.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the door to open?",
+    "options": [
+      "A person swiping a card beside the door",
+      "A person pushing the door",
+      "Both a and b",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010029_Clip_7.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the door to open?",
+    "options": [
+      "A person scanning a card beside the door",
+      "A person rotating the door handle and pushing the door",
+      "Both a and b",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010030_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "When the first person walked up to the transparent door, why did it open?",
+    "options": [
+      "The person scanned a card beside the door",
+      "The door detects the person and automatically opens",
+      "The person clicked a button beside the door",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010029_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "Why does the man wearing the black outfit near the door push a small card against the black object on the white wall beside the door?",
+    "options": [
+      "To change the color of the wall",
+      "To break the door open",
+      "To gain access to the room and unlock the door",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010069_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "Did two people in the video tailgate?",
+    "options": [
+      "Yes",
+      "No"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010011_Clip_9.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the people who entered the room to close the door twice?",
+    "options": [
+      "maintain privacy",
+      "avoid distractions",
+      "focus on work",
+      "all of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010011_Clip_9.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the third person not to punch his card while entering the room?",
+    "options": [
+      "forgot his card",
+      "had no card",
+      "Forgot to punch the card",
+      "all of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "GX010011_Clip_4.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the door to open?",
+    "options": [
+      "A man swiping a card beside the door",
+      "A man rotating the door handle and pushing the door",
+      "Both a and b",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  }
+]

data/vqa/data_jsons/annotations/metrics_temporal_wo_ss.json

@@ -0,0 +1,36 @@
+[
+  {
+    "q_uid": "concat_wh_52_0_0.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the box to fall?",
+    "options": [
+      "The black object under the box moves away",
+      "A person hits the box",
+      "An object hits the box",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  },
+  {
+    "q_uid": "concat_wh_52_0_1.mp4",
+    "industry": "",
+    "event_type": "",
+    "start_time": null,
+    "end_time": null,
+    "video_duration": null,
+    "task_type": "",
+    "question": "What caused the box to fall?",
+    "options": [
+      "The box is not properly placed on the moving black object",
+      "A person hitting the box",
+      "An object hits the box",
+      "None of the above"
+    ],
+    "dimension": "Temporal reasoning"
+  }
+]