Triple
T14854444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Give It 2 Me music video |
E349314
|
entity |
| Predicate | cameraWork |
P20442
|
FINISHED |
| Object | dynamic |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: dynamic | Statement: [Give It 2 Me music video, cameraWork, dynamic]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraWork Context triple: [Give It 2 Me music video, cameraWork, dynamic]
-
A.
cameraConfiguration
Indicates the specific setup or arrangement of a camera’s parameters or components in a given context.
-
B.
cameraStyle
chosen
Indicates the characteristic visual approach or technique used by a camera in capturing or presenting imagery.
-
C.
supportsCameraControl
Indicates that one entity provides functionality for another entity to remotely manage or adjust camera settings or operations.
-
D.
cameraTechnology
Indicates the type or characteristics of camera-related technology associated with an entity.
-
E.
frontCameraFeature
Indicates that an entity has a specified feature, capability, or characteristic associated with its front-facing camera.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded44318f0819080b6c599f2d3474f |
completed | April 14, 2026, 11:56 p.m. |
| PD | Predicate disambiguation | batch_69de8c1798c08190b433e9ad21e41a42 |
completed | April 14, 2026, 6:48 p.m. |
Created at: April 10, 2026, 1:54 a.m.