Triple
T30358370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-mount |
E772205
|
entity |
| Predicate | supportsInBodyImageStabilizationCameras |
P207244
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Fujifilm X-mount, supportsInBodyImageStabilizationCameras, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInBodyImageStabilizationCameras Context triple: [Fujifilm X-mount, supportsInBodyImageStabilizationCameras, yes]
-
A.
hasOpticalImageStabilization
Indicates that a device or component includes a feature that reduces image blur caused by camera movement during capture.
-
B.
compatibleCameraType
Indicates that one entity is a type of camera that can properly function or be used in conjunction with another entity.
-
C.
hasWideCamera
Indicates that an entity is equipped with or features a wide-angle camera.
-
D.
gimbalCapability
Indicates the ability of a system or device to support and control a gimbal’s movement or stabilization functions.
-
E.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified camera.
- F. None of above. chosen
Provenance (4 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 7:57 p.m.