Triple
T4845555
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Utah Stars |
E108279
|
entity |
| Predicate | notablePlayer |
P304
|
FINISHED |
| Object | Ron Boone |
E115548
|
NE 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: Ron Boone | Statement: [Utah Stars, notablePlayer, Ron Boone]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ron Boone Context triple: [Utah Stars, notablePlayer, Ron Boone]
-
A.
Ron Boone
chosen
Ron Boone is a former American professional basketball guard best known for his durability and scoring in the ABA and NBA, particularly with the Utah Stars.
-
B.
James Gardner
James Gardner is a relatively common personal name shared by multiple notable individuals across fields such as politics, the arts, and academia.
-
C.
Warren Foster
Warren Foster was an American animation writer best known for his influential work on classic Warner Bros. cartoons, including many featuring characters like Foghorn Leghorn.
-
D.
Robert Davi
Robert Davi is an American actor, singer, and director best known for his tough-guy roles in films such as "Die Hard" and the James Bond movie "Licence to Kill."
-
E.
Timothy Busfield
Timothy Busfield is an American actor and director best known for his roles in television series such as "thirtysomething," "The West Wing," and various film and stage productions.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69bd4409b264819085ab855f3eb5381a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d020e5c8190aa9ceb4258e713c3 |
completed | March 20, 2026, 3:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be67d70dd0819094b6b2906a9d03b5 |
completed | March 21, 2026, 9:41 a.m. |
Created at: March 20, 2026, 1:25 p.m.