Triple
T8082734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Apple Store, Upper West Side, New York City |
E188655
|
entity |
| Predicate | brandColorAssociation |
P27889
|
FINISHED |
| Object | white |
—
|
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: white | Statement: [Apple Store, Upper West Side, New York City, brandColorAssociation, white]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandColorAssociation Context triple: [Apple Store, Upper West Side, New York City, brandColorAssociation, white]
-
A.
bandColor
Indicates the color associated with a band, such as a stripe, ring, or marking on an object.
-
B.
associatedColour
Indicates that one entity is linked to another as its characteristic or representative colour.
-
C.
corporateColor
chosen
Indicates the official color or color scheme that represents a corporation’s brand or identity.
-
D.
liveryColors
Indicates the specific set of colors used as the official or characteristic color scheme associated with an entity (such as a brand, organization, or vehicle).
-
E.
usesBrandColor
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415cb4688190920868317e77bbff |
completed | March 31, 2026, 3:37 a.m. |
| PD | Predicate disambiguation | batch_69cb049f1614819087360d1a4c6f0faa |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:28 p.m.