Triple
T33999068
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FGC Línies Urbanes |
E871764
|
entity |
| Predicate | usesBrandingColor |
P67963
|
FINISHED |
| Object | FGC corporate colors |
—
|
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: FGC corporate colors | Statement: [FGC Línies Urbanes, usesBrandingColor, FGC corporate colors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBrandingColor Context triple: [FGC Línies Urbanes, usesBrandingColor, FGC corporate colors]
-
A.
usesBrandColor
chosen
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
-
B.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
C.
serviceBrandColor
Indicates the association between a service and the color used to represent its brand identity.
-
D.
usesBrandCharacter
Indicates that one entity employs or features another entity’s brand character (such as a mascot or branded persona) in its materials, products, or communications.
-
E.
usesSignageColorSystem
Indicates that an entity employs a specific color-based signage system to convey information, instructions, or guidance.
- 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f70fb4f18c819099ef6d9177b7d205 |
completed | May 3, 2026, 9:04 a.m. |
| PD | Predicate disambiguation | batch_69f70f3a54d481909ba6bdda3647b761 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:50 a.m.