Triple
T30644218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 50mm f/1.2 GM |
E780073
|
entity |
| Predicate | apertureBlades |
P168191
|
FINISHED |
| Object | 11 rounded blades |
—
|
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: 11 rounded blades | Statement: [Sony FE 50mm f/1.2 GM, apertureBlades, 11 rounded blades]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apertureBlades Context triple: [Sony FE 50mm f/1.2 GM, apertureBlades, 11 rounded blades]
-
A.
hasApertureShape
Indicates that an entity’s aperture (opening) has a specific geometric or descriptive shape.
-
B.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
-
C.
hasApertureClass
Indicates that one entity is classified according to a specific aperture category or class of another entity.
-
D.
hasBladeCount
chosen
Indicates that an object or device is associated with a specific number of blades.
-
E.
hasBayerStars
Indicates that an astronomical object is associated with one or more stars identified by their Bayer designations.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:29 p.m.