Triple
T12047411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPad Air (4th generation) |
E286821
|
entity |
| Predicate | wideColorGamut |
P31543
|
FINISHED |
| Object | P3 |
—
|
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 | Statement: [iPad Air (4th generation), wideColorGamut, P3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wideColorGamut Context triple: [iPad Air (4th generation), wideColorGamut, P3]
-
A.
supportsWideColorGamut
chosen
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
B.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
C.
supportsHDRStandard
Indicates that one entity is compatible with and can correctly handle or implement a specified HDR (High Dynamic Range) standard defined by another entity.
-
D.
supportsHDRFormat
Indicates that one entity is capable of handling, displaying, or processing content encoded in a specified High Dynamic Range (HDR) format for another entity.
-
E.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bac9e08190aa1a99c835f29542 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.