Triple
T9502535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α1 |
E229179
|
entity |
| Predicate | inBodyImageStabilization |
P17639
|
FINISHED |
| Object | 5-axis IBIS |
—
|
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: 5-axis IBIS | Statement: [Sony α1, inBodyImageStabilization, 5-axis IBIS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inBodyImageStabilization Context triple: [Sony α1, inBodyImageStabilization, 5-axis IBIS]
-
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.
supportsCameraControl
Indicates that one entity provides functionality for another entity to remotely manage or adjust camera settings or operations.
-
D.
hasWideCamera
Indicates that an entity is equipped with or features a wide-angle camera.
-
E.
hasInnerSelfieCamera
Indicates that an object (typically a device) is equipped with a front-facing or inward-facing selfie 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983ea6048190a2d7924c8e6d1fbc |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
Created at: March 30, 2026, 7:57 p.m.