Triple
T30358103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EF lens mount |
E772200
|
entity |
| Predicate | compatibilityWithFDLenses |
P180965
|
FINISHED |
| Object | not natively compatible |
—
|
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: not natively compatible | Statement: [Canon EF lens mount, compatibilityWithFDLenses, not natively compatible]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compatibilityWithFDLenses Context triple: [Canon EF lens mount, compatibilityWithFDLenses, not natively compatible]
-
A.
usesAsLens
Indicates that one entity employs another entity as a lens or optical element through which to view, focus, or modify light or images.
-
B.
supportsInterchangeableLenses
Indicates that one entity is capable of using or accommodating different lenses that can be removed and replaced interchangeably.
-
C.
canUseFocalReducer
Indicates that an entity is capable of using a focal reducer in relation to another entity or context.
-
D.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
E.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f75dc25fa08190b371faf36d9fb72c |
completed | May 3, 2026, 2:37 p.m. |
| PD | Predicate disambiguation | batch_69f758586534819083e91172f4bf5098 |
completed | May 3, 2026, 2:14 p.m. |
| PDg | Predicate description generation | batch_69f75dc140c4819085063d6c4c36ca61 |
completed | May 3, 2026, 2:37 p.m. |
Created at: April 29, 2026, 7:57 p.m.