Triple
T30358356
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-mount |
E772205
|
entity |
| Predicate | usedInCameraType |
P182842
|
FINISHED |
| Object | mirrorless digital 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: mirrorless digital camera | Statement: [Fujifilm X-mount, usedInCameraType, mirrorless digital camera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedInCameraType Context triple: [Fujifilm X-mount, usedInCameraType, mirrorless digital camera]
-
A.
usesCameraType
Indicates that one entity employs or operates a specific type or category of camera.
-
B.
compatibleCameraType
chosen
Indicates that one entity is a type of camera that can properly function or be used in conjunction with another entity.
-
C.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified camera.
-
D.
tipoDeCámara
Indicates the specific type or category of camera associated with an entity.
-
E.
meetsInCamera
Indicates that two or more entities are physically present together in the same camera frame or shot at the same time.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd592e48cc81909d754cc6c4bd99ae |
completed | May 8, 2026, 3:31 a.m. |
| PD | Predicate disambiguation | batch_69fd58b7f9b881909dc099b28d567784 |
completed | May 8, 2026, 3:30 a.m. |
Created at: April 29, 2026, 7:57 p.m.