Triple
T12164741
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 15 Pro |
E289801
|
entity |
| Predicate | mainCameraResolution |
P17636
|
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 Pro, mainCameraResolution, 48 MP]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainCameraResolution Context triple: [iPhone 15 Pro, mainCameraResolution, 48 MP]
-
A.
frontCameraResolution
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
-
B.
rearCameraMainResolution
chosen
Indicates the primary resolution (in megapixels or similar units) of a device’s main rear-facing camera.
-
C.
mainResolution
Indicates that one resolution is the primary or most important resolution associated with a given context or entity.
-
D.
viewfinderResolution
Indicates the resolution or level of detail provided by a device’s viewfinder display.
-
E.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915d7109481908bf5fe512bba3c89 |
completed | April 10, 2026, 3:23 p.m. |
| PD | Predicate disambiguation | batch_69d9150c18148190bf8152189c0e5fca |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.