Triple
T30481908
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 85mm f/1.4 GM |
E775609
|
entity |
| Predicate | focusHoldButton |
P180968
|
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 85mm f/1.4 GM, focusHoldButton, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusHoldButton Context triple: [Sony FE 85mm f/1.4 GM, focusHoldButton, yes]
-
A.
focusShift
Indicates a change in attention or emphasis from one entity or topic to another.
-
B.
focusOf
Indicates that one entity is the primary subject, target, or center of attention, activity, or interest for another entity.
-
C.
focusMechanism
Indicates the method or process by which attention or emphasis is directed toward a particular entity or aspect within a context.
-
D.
holdingEffect
Indicates that one entity is maintaining possession or control of another entity, resulting in a particular effect or state during the period of holding.
-
E.
focusFeature
Indicates that one entity is the primary or emphasized feature, aspect, or attribute being highlighted or concentrated on in relation to another.
- 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_69f22497341481909c21ba329fadaa6b |
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, 8:12 p.m.