Triple
T30358525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 200-600mm f/5.6-6.3 G OSS |
E772209
|
entity |
| Predicate | autofocus |
P85619
|
FINISHED |
| Object | internal focusing |
—
|
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: internal focusing | Statement: [Sony FE 200-600mm f/5.6-6.3 G OSS, autofocus, internal focusing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: autofocus Context triple: [Sony FE 200-600mm f/5.6-6.3 G OSS, autofocus, internal focusing]
-
A.
autofocusSystem
chosen
Indicates that there is an autofocus mechanism or method used to automatically adjust focus in an imaging or optical system.
-
B.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
C.
trimFocus
Indicates that an entity’s attention or emphasis is narrowed or adjusted to concentrate more specifically on a particular target or subset of interest.
-
D.
canonicalFocus
Indicates that one entity is the primary or most representative focus or point of attention in relation to another entity.
-
E.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f682417ec08190982dd9acf7219742 |
completed | May 2, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69f67e40af9881908de3a4aa15f70a83 |
completed | May 2, 2026, 10:44 p.m. |
Created at: April 29, 2026, 7:57 p.m.