Triple
T30428138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canon EF-M lens mount |
E774088
|
entity |
| Predicate | supportsLensCorrectionDataCommunication |
P207272
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Canon EF-M lens mount, supportsLensCorrectionDataCommunication, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLensCorrectionDataCommunication Context triple: [Canon EF-M lens mount, supportsLensCorrectionDataCommunication, yes]
-
A.
supportsHardwareCalibration
Indicates that one entity provides the capability or functionality to perform calibration operations on another entity’s hardware.
-
B.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
C.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
D.
hasOpticalFeature
Indicates that an entity possesses a specific optical characteristic or component, such as a visual property, element, or feature related to light or vision.
-
E.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified 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_69f22491ba248190b9a4776ca8e42d02 |
completed | April 29, 2026, 3:32 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, 8:06 p.m.