Triple
T19451096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 15 series |
E486614
|
entity |
| Predicate | mainCameraResolutionStandardModels |
P103408
|
FINISHED |
| Object | 48 MP |
—
|
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: 48 MP | Statement: [iPhone 15 series, mainCameraResolutionStandardModels, 48 MP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCameraResolutionStandardModels Context triple: [iPhone 15 series, mainCameraResolutionStandardModels, 48 MP]
-
A.
hasCameraResolution
chosen
Indicates that an entity is associated with a specific camera resolution value or specification.
-
B.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
C.
frontCameraResolution
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
-
D.
typicalInputResolution
Indicates the usual or standard resolution at which input is expected or typically processed.
-
E.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338db7c081908793f23592ebef6b |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.