Triple
T30842933
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leica screw-mount lenses (via adapter on M bodies) |
E785559
|
entity |
| Predicate | compatibleWithCameraMount |
P33676
|
FINISHED |
| Object | Leica M mount |
—
|
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: Leica M mount | Statement: [Leica screw-mount lenses (via adapter on M bodies), compatibleWithCameraMount, Leica M mount]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compatibleWithCameraMount Context triple: [Leica screw-mount lenses (via adapter on M bodies), compatibleWithCameraMount, Leica M mount]
-
A.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified camera.
-
B.
usesLensMount
chosen
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
C.
compatibleCameraType
Indicates that one entity is a type of camera that can properly function or be used in conjunction with another entity.
-
D.
sightMounting
Indicates that an entity is equipped with or has a sighting device installed or mounted onto it.
-
E.
typeOfGunMount
Indicates the specific kind or configuration of gun mounting used to support or attach a gun.
- 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_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: April 29, 2026, 8:45 p.m.