Triple
T30532315
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 24mm f/1.4 GM |
E777037
|
entity |
| Predicate | autofocusMotorType |
P8442
|
FINISHED |
| Object | Direct Drive SSM |
—
|
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: Direct Drive SSM | Statement: [Sony FE 24mm f/1.4 GM, autofocusMotorType, Direct Drive SSM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: autofocusMotorType Context triple: [Sony FE 24mm f/1.4 GM, autofocusMotorType, Direct Drive SSM]
-
A.
autofocusSystem
Indicates that there is an autofocus mechanism or method used to automatically adjust focus in an imaging or optical system.
-
B.
electricMotorType
chosen
Indicates the specific kind or category of electric motor associated with an entity.
-
C.
steeringType
Indicates the kind or mechanism of steering control used to direct the movement of an entity.
-
D.
autofocusPoints
Indicates the relationship between a camera (or imaging device) and the specific focus points it can automatically select or use for focusing.
-
E.
eraFocus
Indicates a temporal emphasis where something is primarily concerned with, centered on, or characteristic of a particular historical era or time period.
- 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_69f2249c11508190ae7e955755ccfb01 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a16debc8190a12f5f65ced055d7 |
completed | May 2, 2026, 11:34 p.m. |
| PD | Predicate disambiguation | batch_69f6860def1c81909d79e1f088c4b5e5 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:18 p.m.