Triple
T30357984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Minolta A-mount lenses |
E772197
|
entity |
| Predicate | hasFocalLengthRange |
P169099
|
FINISHED |
| Object | ultra-wide-angle to super-telephoto |
—
|
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: ultra-wide-angle to super-telephoto | Statement: [Minolta A-mount lenses, hasFocalLengthRange, ultra-wide-angle to super-telephoto]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFocalLengthRange Context triple: [Minolta A-mount lenses, hasFocalLengthRange, ultra-wide-angle to super-telephoto]
-
A.
focalLengthRange
chosen
Indicates the range of focal lengths over which an optical device (such as a lens) can operate or be adjusted.
-
B.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
-
C.
hasLongFocalLength
Indicates that one entity possesses or is characterized by a focal length that is relatively long compared to a standard or reference.
-
D.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
E.
maximumFocalLength
Indicates the greatest focal length value that an optical device or system can achieve.
- 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_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: April 29, 2026, 7:57 p.m.