Triple
T2604284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carabao |
E58619
|
entity |
| Predicate | hasSponsorshipType |
P2590
|
FINISHED |
| Object | title sponsorship |
—
|
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: title sponsorship | Statement: [Carabao, hasSponsorshipType, title sponsorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSponsorshipType Context triple: [Carabao, hasSponsorshipType, title sponsorship]
-
A.
hasSponsor
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
B.
hasPartnershipType
Indicates the specific kind or category of partnership relationship that exists between entities.
-
C.
hasAffiliationType
Indicates that one entity is connected to another through a specified kind or category of affiliation or association.
-
D.
sponsoringOrganizationType
Indicates the kind or category of organization that provides sponsorship or support in the described relationship or activity.
-
E.
sponsorType
chosen
Indicates the specific role or category of sponsorship that an entity provides in relation to another entity or event.
- 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_69ab4ac3523881909679750c9f8c2dec |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8def9bc8190b2e013abffc7b191 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd80ab7248190ba06ba14fe4c5638 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:49 p.m.