Triple
T2510233
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Studio Display |
E52682
|
entity |
| Predicate | brightnessTypical |
P30545
|
FINISHED |
| Object | 600 nits |
—
|
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: 600 nits | Statement: [Apple Studio Display, brightnessTypical, 600 nits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brightnessTypical Context triple: [Apple Studio Display, brightnessTypical, 600 nits]
-
A.
lightRange
Indicates the distance or area over which a light source effectively emits or illuminates.
-
B.
apparentBrightness
Indicates how bright one object appears from the perspective or location of another, regardless of its actual intrinsic luminosity.
-
C.
lightLevel
Indicates the intensity or amount of light present in a given context or environment.
-
D.
typicalColorDescription
Indicates the usual or characteristic color associated with an entity.
-
E.
lightingCharacteristic
chosen
Indicates the specific qualities or properties of how something is lit, such as brightness, color, direction, or style of illumination.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.