Triple
T9214941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leica rangefinder camera |
E221217
|
entity |
| Predicate | supportsInterchangeableLenses |
P86895
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Leica rangefinder camera, supportsInterchangeableLenses, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInterchangeableLenses Context triple: [Leica rangefinder camera, supportsInterchangeableLenses, true]
-
A.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
B.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
C.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
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.
cameraLensType
Indicates the specific type or category of lens used or associated with a camera.
- 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_69ca83eae42c8190a0ea9e040710a277 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda0830a8819096a186ed2e976cba |
completed | April 1, 2026, 8:40 a.m. |
| PD | Predicate disambiguation | batch_69cc660ce23c81909c7bbe10f4a05f36 |
completed | April 1, 2026, 12:25 a.m. |
| PDg | Predicate description generation | batch_69cc687067fc81909da2d78fda0cdcfb |
completed | April 1, 2026, 12:36 a.m. |
Created at: March 30, 2026, 7:27 p.m.