Triple
T10436157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lithuanian Basketball League |
E246043
|
entity |
| Predicate | hasSponsorshipDeals |
P35686
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Lithuanian Basketball League, hasSponsorshipDeals, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSponsorshipDeals Context triple: [Lithuanian Basketball League, hasSponsorshipDeals, yes]
-
A.
hasSponsor
chosen
Indicates that one entity financially or otherwise supports another entity, typically in exchange for recognition or other benefits.
-
B.
sponsorshipDealStart
Indicates the point in time when a sponsorship agreement between parties officially begins.
-
C.
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.
-
D.
hasNotableDeal
Indicates that an entity is involved in a significant or noteworthy agreement, contract, or transaction with another entity.
-
E.
hasDealingsIn
Indicates that an entity engages in activities, transactions, or business related to a particular domain, location, or subject.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea843f1c8190afca4a42bc364468 |
completed | April 7, 2026, 11:29 a.m. |
| PD | Predicate disambiguation | batch_69d4dfbc546881908f312c66ee195f79 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:14 p.m.