Triple
T19451383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | iPhone 7 |
E486620
|
entity |
| Predicate | hasWideColorDisplay |
P31543
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [iPhone 7, hasWideColorDisplay, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWideColorDisplay Context triple: [iPhone 7, hasWideColorDisplay, yes]
-
A.
supportsWideColorGamut
chosen
Indicates that one entity provides or enables compatibility with a wide color gamut capability for another entity or context.
-
B.
hasColorDisplay
Indicates that an entity is equipped with a display capable of showing colors rather than only monochrome output.
-
C.
hasBetterColorReproductionThan
Indicates that one entity produces more accurate or higher-quality color representation than another entity.
-
D.
supportsColorSampling
Indicates that one entity can perform or accommodate color sampling operations on another entity or its data.
-
E.
hasPhysicalDisplays
Indicates that an entity possesses one or more tangible, visible display units or interfaces.
- 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_69d8e8d7ad488190a3373045029b0f3b |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6338db7c081908793f23592ebef6b |
completed | April 20, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.