Triple
T30842902
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leica M lenses |
E785558
|
entity |
| Predicate | typicalFocalLengths |
P207312
|
FINISHED |
| Object | wide-angle |
—
|
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: wide-angle | Statement: [Leica M lenses, typicalFocalLengths, wide-angle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFocalLengths Context triple: [Leica M lenses, typicalFocalLengths, wide-angle]
-
A.
focalLengthRange
Indicates the range of focal lengths over which an optical device (such as a lens) can operate or be adjusted.
-
B.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
C.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
D.
hasLongFocalLength
Indicates that one entity possesses or is characterized by a focal length that is relatively long compared to a standard or reference.
-
E.
maximumFocalLength
Indicates the greatest focal length value that an optical device or system can achieve.
- 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_69f224b850848190a4af4ccf8ddadcdf |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e2fac0819089b522db3260028c |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7ee0388190a29faeb5cdb0950a |
completed | May 12, 2026, 7:16 p.m. |
Created at: April 29, 2026, 8:45 p.m.