Triple
T26781660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Air Transport Leipzig |
E670263
|
entity |
| Predicate | associatedBrandColor |
P65875
|
FINISHED |
| Object | yellow |
—
|
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: yellow | Statement: [European Air Transport Leipzig, associatedBrandColor, yellow]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedBrandColor Context triple: [European Air Transport Leipzig, associatedBrandColor, yellow]
-
A.
serviceBrandColor
Indicates the association between a service and the color used to represent its brand identity.
-
B.
usesBrandColor
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
-
C.
associatedColour
chosen
Indicates that one entity is linked to another as its characteristic or representative colour.
-
D.
corporateColor
Indicates the official color or color scheme that represents a corporation’s brand or identity.
-
E.
officialColor
Indicates the color that is formally designated or recognized as the official one for an 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69ff70ecc1a481909571b18d56d982b8 |
completed | May 9, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69ff70322a3c8190837840ea42cd3093 |
completed | May 9, 2026, 5:34 p.m. |
Created at: April 27, 2026, 4:09 a.m.