Triple
T32069280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rust-eze Racing |
E818966
|
entity |
| Predicate | sponsorLogoPlacement |
P48677
|
FINISHED |
| Object | Lightning McQueen’s hood |
—
|
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: Lightning McQueen’s hood | Statement: [Rust-eze Racing, sponsorLogoPlacement, Lightning McQueen’s hood]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorLogoPlacement Context triple: [Rust-eze Racing, sponsorLogoPlacement, Lightning McQueen’s hood]
-
A.
sponsorPlacement
Indicates that one entity financially supports or endorses another entity in exchange for a specified form of promotional placement.
-
B.
logoPlacement
chosen
Indicates the spatial or contextual position where a logo is displayed or applied in relation to another object, surface, or medium.
-
C.
sponsorBrandType
Indicates the type or category of brand that is acting as a sponsor in the relationship.
-
D.
sponsorshipBrand
Indicates that one entity serves as a sponsoring brand for another entity, typically providing support, funding, or endorsement.
-
E.
sponsorPosition
Indicates that one entity financially or otherwise supports another entity in holding or obtaining a particular position, role, or placement.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 12:23 a.m.