Triple
T3568792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pixel XL |
E75517
|
entity |
| Predicate | rearCameraFeatures |
P29799
|
FINISHED |
| Object | phase detection autofocus |
—
|
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: phase detection autofocus | Statement: [Pixel XL, rearCameraFeatures, phase detection autofocus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraFeatures Context triple: [Pixel XL, rearCameraFeatures, phase detection autofocus]
-
A.
rearCameraFeature
chosen
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
B.
rearCameraUltraWideAperture
Indicates the aperture size specification of a device’s ultra-wide rear camera lens.
-
C.
rearCameraUltraWideResolution
Indicates the resolution specification of the device’s rear ultra-wide camera.
-
D.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
E.
rearCameraCount
Indicates the number of camera units located on the rear side of a device.
- 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_69ad85d512708190829c8b2d3a2ccfb8 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0c083ac8190a71cd9ede2114cac |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb8364d848190a96a9bc7a6126af2 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.