Triple
T11243777
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Pro (11-inch, 2nd generation) |
E266144
|
entity |
| Predicate | rearCameraType |
P98655
|
FINISHED |
| Object | 12 MP wide camera |
—
|
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: 12 MP wide camera | Statement: [iPad Pro (11-inch, 2nd generation), rearCameraType, 12 MP wide camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraType Context triple: [iPad Pro (11-inch, 2nd generation), rearCameraType, 12 MP wide camera]
-
A.
rearCameraFeature
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
B.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
C.
rearCameraUltraWideAperture
Indicates the aperture size specification of a device’s ultra-wide rear camera lens.
-
D.
rearCameraCount
Indicates the number of camera units located on the rear side of a device.
-
E.
rearCameraUltraWideResolution
Indicates the resolution specification of the device’s rear ultra-wide camera.
- F. None of above. chosen
Provenance (4 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. |
| PDg | Predicate description generation | batch_69d796cf74308190a5b29d0dd82954a2 |
completed | April 9, 2026, 12:08 p.m. |
Created at: April 8, 2026, 9:30 p.m.