Triple
T30698733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 100-400mm f/4.5-5.6 GM OSS |
E781549
|
entity |
| Predicate | supportsInCameraCorrections |
P207301
|
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: [Sony FE 100-400mm f/4.5-5.6 GM OSS, supportsInCameraCorrections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsInCameraCorrections Context triple: [Sony FE 100-400mm f/4.5-5.6 GM OSS, supportsInCameraCorrections, yes]
-
A.
supportsCameraControl
Indicates that one entity provides functionality for another entity to remotely manage or adjust camera settings or operations.
-
B.
compatibleWithCamera
Indicates that one item can function correctly or be used without conflict together with a specified camera.
-
C.
supportsHardwareCalibration
Indicates that one entity provides the capability or functionality to perform calibration operations on another entity’s hardware.
-
D.
supportsCinematicMode
Indicates that one entity provides or enables a cinematic mode feature for another entity.
-
E.
compatibleCameraType
Indicates that one entity is a type of camera that can properly function or be used in conjunction with another 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_69f224ab24e08190991d6edb6df58e8b |
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, 8:34 p.m.