Triple
T30842938
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leica screw-mount lenses (via adapter on M bodies) |
E785559
|
entity |
| Predicate | typicalFocalLengthsInclude |
P44359
|
FINISHED |
| Object | 28mm |
—
|
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: 28mm | Statement: [Leica screw-mount lenses (via adapter on M bodies), typicalFocalLengthsInclude, 28mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFocalLengthsInclude Context triple: [Leica screw-mount lenses (via adapter on M bodies), typicalFocalLengthsInclude, 28mm]
-
A.
focalLengthRange
Indicates the range of focal lengths over which an optical device (such as a lens) can operate or be adjusted.
-
B.
focalLength
chosen
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
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.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
E.
tipoDeCámara
Indicates the specific type or category of camera associated with an entity.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 8:45 p.m.