Triple
T30358336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-mount |
E772205
|
entity |
| Predicate | introducedWithCamera |
P191583
|
FINISHED |
| Object | Fujifilm X-Pro1 |
—
|
NE NERFINISHED |
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: Fujifilm X-Pro1 | Statement: [Fujifilm X-mount, introducedWithCamera, Fujifilm X-Pro1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedWithCamera Context triple: [Fujifilm X-mount, introducedWithCamera, Fujifilm X-Pro1]
-
A.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified camera.
-
B.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
C.
usesCameraType
Indicates that one entity employs or operates a specific type or category of camera.
-
D.
compatibleCameraType
Indicates that one entity is a type of camera that can properly function or be used in conjunction with another 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. 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_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce28a74508190aab36551094e8226 |
completed | May 7, 2026, 7:05 p.m. |
Created at: April 29, 2026, 7:57 p.m.