Triple
T13068921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian Hockey League |
E329401
|
entity |
| Predicate | hasCommercialSponsorships |
P35686
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Austrian Hockey League, hasCommercialSponsorships, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommercialSponsorships Context triple: [Austrian Hockey League, hasCommercialSponsorships, true]
-
A.
hasSponsor
chosen
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
B.
hasTitleSponsor
Indicates that one entity serves as the primary (title) sponsor for another entity, typically giving its name to the sponsored event, organization, or property.
-
C.
doesNotSponsor
Indicates that one entity does not provide sponsorship or support to another entity.
-
D.
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.
-
E.
sponsorshipEnded
Indicates that a previously existing sponsorship relationship between entities has been terminated or has come to an end.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ec8ba48190baf52c7823482680 |
completed | April 10, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69d9803d46688190bac6b7d208f08d01 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9 p.m.