Triple
T1775270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacBook Air (M1, 2020) |
E38962
|
entity |
| Predicate | supportsWideColorGamut |
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: [MacBook Air (M1, 2020), supportsWideColorGamut, P3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsWideColorGamut Context triple: [MacBook Air (M1, 2020), supportsWideColorGamut, P3]
-
A.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
B.
supportsDisplayPortAltMode
Indicates that one entity is capable of transmitting video and audio using the DisplayPort Alternate Mode over a USB-C or similar connection to another entity.
-
C.
hasColorOption
Indicates that an entity offers or supports a particular color as one of its selectable options.
-
D.
assumedDisplayGamma
Indicates that a specific gamma value is presumed to characterize the display’s tone response or brightness mapping behavior.
-
E.
displayResolution
Indicates the relationship specifying the width and height dimensions at which visual content is rendered or shown on a display.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab17e368048190b7b73d156400f772 |
completed | March 6, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69aa61cd4c1c8190a8dff391f5642bfe |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab17d0a644819087e6ce39d6c60da5 |
completed | March 6, 2026, 6:07 p.m. |
Created at: March 4, 2026, 7:31 p.m.