Triple
T18911565
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pop-Tarts Bowl |
E462619
|
entity |
| Predicate | hasCommercialSponsorship |
P35686
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Pop-Tarts Bowl, hasCommercialSponsorship, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialSponsorship Context triple: [Pop-Tarts Bowl, hasCommercialSponsorship, yes]
-
A.
hasSponsor
chosen
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
B.
hasFictionalSponsor
Indicates that an entity is sponsored or endorsed by a sponsor that is fictional rather than real.
-
C.
hasTitleSponsor
Indicates that one entity serves as the primary (title) sponsor for another entity, typically giving its name to the sponsored event, organization, or property.
-
D.
hasCommercialAppeal
Indicates that something possesses qualities likely to attract buyers or generate profitable market interest.
-
E.
doesNotSponsor
Indicates that one entity does not provide sponsorship or support to another 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_69d8dcfd05bc819088903cca13cc2846 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c6238e288190b30311b5d80beafb |
completed | April 20, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69e4a2e9e6488190ba8df92c8058ed88 |
completed | April 19, 2026, 9:39 a.m. |
Created at: April 10, 2026, 11:58 a.m.