Triple
T14240891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia N82 |
E353000
|
entity |
| Predicate | rearCameraAutofocus |
P29799
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Nokia N82, rearCameraAutofocus, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rearCameraAutofocus Context triple: [Nokia N82, rearCameraAutofocus, true]
-
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.
rearCameraAperture
Indicates the size or f-stop value of the aperture used by a device’s rear-facing camera when capturing images or video.
-
D.
rearCameraType
Indicates the specific kind or configuration of camera system located on the rear side of an object or device.
-
E.
frontCameraFeature
Indicates that an entity has a specified feature, capability, or characteristic associated with its front-facing camera.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6244ad188190b9d9db7914240410 |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:08 a.m.