Triple
T12047417
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Air (4th generation) |
E286821
|
entity |
| Predicate | rearCameraVideoRecording |
P29799
|
FINISHED |
| Object | 4K at 60 fps |
—
|
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: 4K at 60 fps | Statement: [iPad Air (4th generation), rearCameraVideoRecording, 4K at 60 fps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraVideoRecording Context triple: [iPad Air (4th generation), rearCameraVideoRecording, 4K at 60 fps]
-
A.
rearCameraFeature
chosen
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
B.
hasVideoRecording
Indicates that there exists an associated video recording capturing or documenting the referenced entity or event.
-
C.
hasVideoRecordingAvailableOn
Indicates that a video recording of something is accessible or hosted on a specified platform, service, or medium.
-
D.
rearCameraType
Indicates the specific kind or configuration of camera system located on the rear side of an object or device.
-
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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.