Triple
T31008864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nikon Z fc |
E790150
|
entity |
| Predicate | hasHotShoe |
P169832
|
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: [Nikon Z fc, hasHotShoe, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHotShoe Context triple: [Nikon Z fc, hasHotShoe, yes]
-
A.
hasBuiltInFlashHotShoe
Indicates that an entity is equipped with a built-in flash unit that mounts via a hot shoe connection.
-
B.
hotShoe
chosen
Indicates that one entity serves as a hot shoe connection point, providing a standardized mounting and electrical interface for another device.
-
C.
hasDedicatedCameraButton
Indicates that an object or device includes a specific physical button intended solely for activating or controlling the camera function.
-
D.
hasTorch
Indicates that one entity possesses or is currently holding a torch in relation to another context or entity.
-
E.
hotShoeType
Indicates the specific type or standard of hot shoe interface used to connect accessories (such as flashes) to a device.
- 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_69f224c73ca48190a1e46cb58ad4045b |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fcd867f36081908c88c55a6a1404c1 |
completed | May 7, 2026, 6:22 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f47b188190b4cf4b4c748d9d03 |
completed | May 7, 2026, 5:55 p.m. |
Created at: April 29, 2026, 8:57 p.m.