Triple
T1167482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gillette |
E24830
|
entity |
| Predicate | hasSponsored |
P1807
|
FINISHED |
| Object | FIFA World Cup-related campaigns |
—
|
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: FIFA World Cup-related campaigns | Statement: [Gillette, hasSponsored, FIFA World Cup-related campaigns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSponsored Context triple: [Gillette, hasSponsored, FIFA World Cup-related campaigns]
-
A.
sponsorInHouse
Indicates that one entity formally supports, promotes, or funds another entity within the same organization, institution, or internal setting.
-
B.
hasSupporter
Indicates that one entity supports, endorses, or backs another entity.
-
C.
coSponsor
Indicates that an entity jointly supports, endorses, or backs an initiative, proposal, or activity together with one or more others.
-
D.
sponsors
chosen
Indicates that one entity provides financial or material support to another, often in exchange for association, promotion, or fulfillment of certain activities or goals.
-
E.
stateOfSponsor
Indicates the current status or condition of a sponsor in relation to the sponsored entity or activity.
- 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.