Triple
T34802232
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MuchMusic USA |
E1003246
|
entity |
| Predicate | hadBrandingRelationshipWith |
P11989
|
FINISHED |
| Object | MuchMusic (Canada) |
—
|
NE NERFINISHED |
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: MuchMusic (Canada) | Statement: [MuchMusic USA, hadBrandingRelationshipWith, MuchMusic (Canada)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadBrandingRelationshipWith Context triple: [MuchMusic USA, hadBrandingRelationshipWith, MuchMusic (Canada)]
-
A.
hasBranding
chosen
Indicates that one entity carries, displays, or is associated with the brand identity of another entity.
-
B.
sponsorshipBrandingSince
Indicates that one entity has been publicly branded or presented as sponsored by another entity starting from a specific point in time and continuing thereafter.
-
C.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
-
D.
hasCoBrand
Indicates that two brands are jointly associated or partnered in offering a product, service, or marketing initiative.
-
E.
hasBrandRole
Indicates that an entity holds a specific functional or organizational role in relation to a particular brand.
- 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_69f76db543808190b188c6c86a91491b |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f77a8adccc8190a80bb421f7a04e82 |
completed | May 3, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69f7795b1abc8190823664d1caa94649 |
completed | May 3, 2026, 4:35 p.m. |
Created at: May 3, 2026, 3:59 p.m.