Triple
T37945983
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia 5800 XpressMusic |
E946606
|
entity |
| Predicate | cameraRearFeatures |
P29799
|
FINISHED |
| Object | Carl Zeiss optics |
—
|
NE NERFINISHED |
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: Carl Zeiss optics | Statement: [Nokia 5800 XpressMusic, cameraRearFeatures, Carl Zeiss optics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraRearFeatures Context triple: [Nokia 5800 XpressMusic, cameraRearFeatures, Carl Zeiss optics]
-
A.
rearCameraFeature
chosen
Indicates that an entity has a specific characteristic, capability, or attribute related to its rear-facing camera.
-
B.
cameraRearMegapixels
Indicates the number of megapixels of a device’s rear-facing camera.
-
C.
rearCameraType
Indicates the specific kind or configuration of camera system located on the rear side of an object or device.
-
D.
frontCameraFeature
Indicates that an entity has a specified feature, capability, or characteristic associated with its front-facing camera.
-
E.
rearCameraUltraWideAperture
Indicates the aperture size specification of a device’s ultra-wide rear camera lens.
- 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_69f76ef531ac8190ae6d99e5786e76ec |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc995dc2481908b3bd4217f8101e7 |
completed | May 6, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69fbc8ee04f08190977b7ad70fc85896 |
completed | May 6, 2026, 11:04 p.m. |
Created at: May 3, 2026, 4:20 p.m.