Triple
T30357988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minolta A-mount lenses |
E772197
|
entity |
| Predicate | hasNotableLens |
P40837
|
FINISHED |
| Object | Minolta AF 50mm f/1.4 |
—
|
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: Minolta AF 50mm f/1.4 | Statement: [Minolta A-mount lenses, hasNotableLens, Minolta AF 50mm f/1.4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableLens Context triple: [Minolta A-mount lenses, hasNotableLens, Minolta AF 50mm f/1.4]
-
A.
hasNativeLensesFrom
Indicates that an entity is originally equipped with or designed to use lenses provided by the referenced source entity.
-
B.
usesLensBrand
chosen
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
C.
hasNotableFeature
Indicates that an entity possesses a specific characteristic, trait, or attribute that is considered significant or noteworthy.
-
D.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
E.
usesAsLens
Indicates that one entity employs another entity as a lens or optical element through which to view, focus, or modify light or images.
- 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_6a00383e868c819098fd17e25fcbdb04 |
completed | May 10, 2026, 7:48 a.m. |
| PD | Predicate disambiguation | batch_6a0037cc59688190b7b9da939a413db3 |
completed | May 10, 2026, 7:46 a.m. |
Created at: April 29, 2026, 7:57 p.m.