Triple
T6049112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Transports publics genevois |
E134742
|
entity |
| Predicate | usesBrandColor |
P67963
|
FINISHED |
| Object | orange |
—
|
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: orange | Statement: [Transports publics genevois, usesBrandColor, orange]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesBrandColor Context triple: [Transports publics genevois, usesBrandColor, orange]
-
A.
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.
-
B.
usedBrand
Indicates that an entity has utilized, applied, or operated a particular brand in some context.
-
C.
hasBrandName
Indicates that an entity is associated with or identified by a specific brand name.
-
D.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
-
E.
usesTransportBrand
Indicates that one entity makes use of a transportation service, vehicle, or system associated with a specific brand.
- 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_69c00876a69881908088a2626d3b2666 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056f387cc8190920b846995761aec |
completed | March 22, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69c049edc6f0819092ca620d9073ad26 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04dbefd1081909795fe1a812b991a |
completed | March 22, 2026, 8:14 p.m. |
Created at: March 22, 2026, 4:09 p.m.