Triple
T8781477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ozzie Silna |
E208738
|
entity |
| Predicate | sportsBusinessDomain |
P71678
|
FINISHED |
| Object | basketball |
—
|
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: basketball | Statement: [Ozzie Silna, sportsBusinessDomain, basketball]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportsBusinessDomain Context triple: [Ozzie Silna, sportsBusinessDomain, basketball]
-
A.
sportIndustry
chosen
Indicates a relationship where an entity is involved in, associated with, or part of the sports industry or sports-related economic sector.
-
B.
sportsRights
Indicates that one entity holds legal rights or permissions related to broadcasting, distributing, or otherwise commercially exploiting a sports event or sports content in relation to another entity.
-
C.
sportsBrand
Indicates that one entity is a sports-related brand or label associated with the other entity.
-
D.
sportsBusinessRole
Indicates a professional role or position that an entity holds within the context of sports business or the sports industry.
-
E.
sportsAttraction
Indicates a relationship where an entity serves as a venue, site, or draw specifically for sports-related activities or events.
- 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_69ca835fbee88190bf625939bac48d7f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5f55b7b08190ab3e18cd634a144b |
completed | March 31, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1aff3881908be6a9cbc9f50461 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:42 p.m.