Triple
T11243779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Pro (11-inch, 2nd generation) |
E266144
|
entity |
| Predicate | frontCameraType |
P58520
|
FINISHED |
| Object | TrueDepth camera system |
—
|
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: TrueDepth camera system | Statement: [iPad Pro (11-inch, 2nd generation), frontCameraType, TrueDepth camera system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: frontCameraType Context triple: [iPad Pro (11-inch, 2nd generation), frontCameraType, TrueDepth camera system]
-
A.
frontCameraResolution
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
-
B.
frontCameraCount
Indicates the number of front-facing cameras associated with an entity.
-
C.
rearCameraFeature
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
D.
usesCameraType
chosen
Indicates that one entity employs or operates a specific type or category of camera.
-
E.
hasOuterSelfieCamera
Indicates that an entity (typically a device) is equipped with a front-facing camera intended for taking selfies.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91b0b808190bc38008bb344d180 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:30 p.m.