Triple
T1167479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gillette |
E24830
|
entity |
| Predicate | associatedWithSportSponsorship |
P790
|
FINISHED |
| Object | American football |
—
|
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: American football | Statement: [Gillette, associatedWithSportSponsorship, American football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithSportSponsorship Context triple: [Gillette, associatedWithSportSponsorship, American football]
-
A.
sponsorSport
chosen
Indicates that one entity financially or materially supports a sport or sporting activity, typically in exchange for promotion or association.
-
B.
alsoSponsorsSport
Indicates that an entity that sponsors one sport also sponsors another sport.
-
C.
sportsSponsored
Indicates that one entity provides financial or material sponsorship to support another entity’s sports-related activities or events.
-
D.
associatedWithTeamSport
Indicates a relationship where an entity is connected to, involved in, or participates in a team-based sport.
-
E.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other 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_69a494082a7c819095004f423f294a64 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bccd75048190b8ce88237c1a748b |
completed | March 1, 2026, 10:25 p.m. |
| PD | Predicate disambiguation | batch_69a4bb548c1481909092626c572d8782 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.