Triple
T10858432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | O2 Academy network |
E256329
|
entity |
| Predicate | hasBrandingFeature |
P48662
|
FINISHED |
| Object | O2 logo on venue signage |
—
|
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: O2 logo on venue signage | Statement: [O2 Academy network, hasBrandingFeature, O2 logo on venue signage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBrandingFeature Context triple: [O2 Academy network, hasBrandingFeature, O2 logo on venue signage]
-
A.
hasBranding
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
B.
brandingFeature
Indicates that one entity serves as a branding-related characteristic, element, or attribute that helps define or distinguish another entity’s brand identity.
-
C.
hasBrandIdentityElement
chosen
Indicates that an entity includes or is associated with a specific component of its overall brand identity (such as a logo, color scheme, or tagline).
-
D.
supportsBrand
Indicates that one entity endorses, promotes, or is compatible with a particular brand.
-
E.
hasBrandType
Indicates that an entity is associated with or categorized under a particular brand type or classification.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751500e248190823a16f2c85ad829 |
completed | April 9, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d70d308dfc81908792f98cfb871392 |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.