Triple
T35565547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huawei Nova 10 |
E1027761
|
entity |
| Predicate | rearCameraDepthSensor |
P182342
|
FINISHED |
| Object | 2 MP depth |
—
|
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: 2 MP depth | Statement: [Huawei Nova 10, rearCameraDepthSensor, 2 MP depth]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraDepthSensor Context triple: [Huawei Nova 10, rearCameraDepthSensor, 2 MP depth]
-
A.
depthRearCameraResolution
chosen
Indicates the resolution at which the device’s rear depth-sensing camera can capture images or data.
-
B.
rearCameraType
Indicates the specific kind or configuration of camera system located on the rear side of an object or device.
-
C.
rearCameraFeature
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
D.
rearCameraSensorSize
Indicates the physical dimensions of the image sensor used by the device’s rear camera.
-
E.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:04 p.m.