Triple
T29910491
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 15-inch MacBook Air (M2) |
E759666
|
entity |
| Predicate | displayColorGamut |
P31543
|
FINISHED |
| Object | P3 wide color |
—
|
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: P3 wide color | Statement: [15-inch MacBook Air (M2), displayColorGamut, P3 wide color]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: displayColorGamut Context triple: [15-inch MacBook Air (M2), displayColorGamut, P3 wide color]
-
A.
supportsWideColorGamut
chosen
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
B.
colorPrimaries
Indicates the primary color components or base colors used to define the color representation of an image or visual signal.
-
C.
colorDisplay
Indicates that one entity presents, shows, or renders the color associated with another entity.
-
D.
assumedDisplayGamma
Indicates that a specific gamma value is presumed to characterize the display’s tone response or brightness mapping behavior.
-
E.
supportsColorProfile
Indicates that one entity is capable of recognizing, handling, or applying the specified color profile associated with another entity.
- 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_69f224600590819085e148a01c056ef6 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67d3624248190a36a9b2d2e9778d4 |
completed | May 2, 2026, 10:39 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 6:10 p.m.