Triple
T38571666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 14 Plus |
E929291
|
entity |
| Predicate | hasSensorShiftOIS |
P17639
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [iPhone 14 Plus, hasSensorShiftOIS, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSensorShiftOIS Context triple: [iPhone 14 Plus, hasSensorShiftOIS, true]
-
A.
hasOpticalImageStabilization
chosen
Indicates that a device or component includes a feature that reduces image blur caused by camera movement during capture.
-
B.
hasOpticalFeature
Indicates that an entity possesses a specific optical characteristic or component, such as a visual property, element, or feature related to light or vision.
-
C.
hasElectronicShutter
Indicates that an entity is equipped with or supports an electronic shutter mechanism for capturing images without a mechanical shutter.
-
D.
hasOIS
Indicates that an entity possesses, is associated with, or is characterized by an OIS (e.g., a specific information system, identifier, or status labeled "OIS").
-
E.
hasWideCamera
Indicates that an entity is equipped with or features a wide-angle 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a00d8ba18808190976682088a02a9a8 |
completed | May 10, 2026, 7:12 p.m. |
| PD | Predicate disambiguation | batch_6a00d85fad64819084f424ec8ecd3b57 |
completed | May 10, 2026, 7:11 p.m. |
Created at: May 3, 2026, 4:32 p.m.