Triple
T28901699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 8 |
E732966
|
entity |
| Predicate | opticalImageStabilization |
P17639
|
FINISHED |
| Object | rear 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: rear camera | Statement: [iPhone 8, opticalImageStabilization, rear camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: opticalImageStabilization Context triple: [iPhone 8, opticalImageStabilization, rear camera]
-
A.
hasOpticalImageStabilization
chosen
Indicates that a device or component includes a feature that reduces image blur caused by camera movement during capture.
-
B.
gimbalCapability
Indicates the ability of a system or device to support and control a gimbal’s movement or stabilization functions.
-
C.
stabilizationCompensation
Indicates a compensatory action or mechanism that counteracts changes or disturbances in order to maintain or restore stability in a system or process.
-
D.
cameraTechnology
Indicates the type or characteristics of camera-related technology associated with an entity.
-
E.
hasOpticalElement
Indicates that one entity includes, contains, or is equipped with a specific optical element as a component or part.
- 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_69f05b08c2008190ac426a035a2ed66d |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f65aa8deec8190b1eef143e10c9598 |
completed | May 2, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69f6576487e081908d802f1caf59c423 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 8:03 a.m.