Triple
T30602726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Huawei P10 |
E778955
|
entity |
| Predicate | primaryCameraAperture |
P44127
|
FINISHED |
| Object | f/2.2 |
—
|
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: f/2.2 | Statement: [Huawei P10, primaryCameraAperture, f/2.2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryCameraAperture Context triple: [Huawei P10, primaryCameraAperture, f/2.2]
-
A.
rearCameraAperture
chosen
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
B.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
C.
rearCameraTelephotoAperture
Indicates the aperture value (light-opening size) of the telephoto lens in the device’s rear camera system.
-
D.
maximumAperture
Indicates the widest opening size that an optical system (such as a lens) can achieve to allow light to pass through.
-
E.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
- 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_69f224a21fc08190abd9d8dd9eb6bb4c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a030f1480148190a5e8c8926ded252c |
completed | May 12, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_6a030e7f5fa481909696733defefcc20 |
completed | May 12, 2026, 11:26 a.m. |
Created at: April 29, 2026, 8:25 p.m.