Triple
T1775300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Air (M1, 2020) |
E38962
|
entity |
| Predicate | cameraResolution |
P17638
|
FINISHED |
| Object | 720p FaceTime HD camera |
—
|
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: 720p FaceTime HD camera | Statement: [MacBook Air (M1, 2020), cameraResolution, 720p FaceTime HD camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraResolution Context triple: [MacBook Air (M1, 2020), cameraResolution, 720p FaceTime HD camera]
-
A.
telephotoCameraResolution
Indicates the image resolution capability of a device’s telephoto camera in a given context.
-
B.
frontCameraResolution
chosen
Indicates the resolution quality or pixel count of a device’s front-facing (selfie) camera.
-
C.
rearCameraMainResolution
Indicates the primary resolution (in megapixels or similar units) of a device’s main rear-facing camera.
-
D.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
-
E.
rearCameraUltraWideResolution
Indicates the resolution specification of the device’s rear ultra-wide 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab17e368048190b7b73d156400f772 |
completed | March 6, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69aa61cd4c1c8190a8dff391f5642bfe |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:31 p.m.