Triple
T21630031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | BP Top 8 |
E533804
|
entity |
| Predicate | sponsorshipNature |
P145302
|
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: [BP Top 8, sponsorshipNature, title sponsorship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sponsorshipNature Context triple: [BP Top 8, sponsorshipNature, title sponsorship]
-
A.
sponsors
Indicates that one entity provides financial or material support to another, often in exchange for association, promotion, or fulfillment of certain activities or goals.
-
B.
sponsorInHouse
Indicates that one entity formally supports, promotes, or funds another entity within the same organization, institution, or internal setting.
-
C.
sponsorshipRenamedFrom
Indicates that a sponsorship currently known by one name previously existed under a different, earlier name.
-
D.
sponsorshipIndustry
Indicates a relationship where one entity sponsors another specifically within a given industry or sector context.
-
E.
sponsorTo
Indicates that one entity provides support, funding, or endorsement to another entity, typically to enable or promote the latter’s activities or initiatives.
- F. None of above. chosen
Provenance (4 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef5215ae3c81909e6dedba23822970 |
completed | April 27, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69e69677b9c48190bf81f795aa8ad74e |
completed | April 20, 2026, 9:11 p.m. |
| PDg | Predicate description generation | batch_69e69cb4bcbc8190a4fc2d508df107be |
completed | April 20, 2026, 9:37 p.m. |
Created at: April 16, 2026, 6:34 p.m.