Triple
T30644216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 50mm f/1.2 GM |
E780073
|
entity |
| Predicate | bokehQuality |
P169653
|
FINISHED |
| Object | creamy bokeh |
—
|
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: creamy bokeh | Statement: [Sony FE 50mm f/1.2 GM, bokehQuality, creamy bokeh]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bokehQuality Context triple: [Sony FE 50mm f/1.2 GM, bokehQuality, creamy bokeh]
-
A.
outputQuality
Indicates the degree to which a produced result or outcome meets desired standards, expectations, or specifications.
-
B.
imageQuality
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
C.
videoQuality
Indicates the level or standard of clarity, resolution, and overall visual fidelity associated with a given video.
-
D.
visualDetail
Indicates that one entity provides or specifies the visual characteristics, features, or appearance details of another entity.
-
E.
surfaceQuality
Indicates the condition or characteristics of an entity’s outer surface, such as its smoothness, roughness, or finish.
- 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_69f224a50ebc81909b961a94c7f66b12 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68a58cd808190bc1cdaa106291084 |
completed | May 2, 2026, 11:35 p.m. |
| PD | Predicate disambiguation | batch_69f67e448a9c8190b591374d98799fe3 |
completed | May 2, 2026, 10:44 p.m. |
| PDg | Predicate description generation | batch_69f67f0353c88190a05b2db449abe0f4 |
completed | May 2, 2026, 10:47 p.m. |
Created at: April 29, 2026, 8:29 p.m.