Triple
T18419119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samir Bannout |
E441973
|
entity |
| Predicate | hasWonCompetition |
P8326
|
FINISHED |
| Object | Mr. Olympia |
—
|
NE NERFINISHED |
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: Mr. Olympia | Statement: [Samir Bannout, hasWonCompetition, Mr. Olympia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. Olympia Context triple: [Samir Bannout, hasWonCompetition, Mr. Olympia]
-
A.
Mr. Olympia
chosen
Mr. Olympia is the premier annual professional bodybuilding competition that crowns the world’s top male bodybuilder.
-
B.
Ms. Olympia
Ms. Olympia is the premier professional women’s bodybuilding competition, regarded as the highest title in female bodybuilding.
-
C.
Mr. Universe
Mr. Universe is the stage name of Greg Universe, the free-spirited former musician and father of Steven in the animated series "Steven Universe."
-
D.
Mr. Universe
Mr. Universe is a stand-up comedy special by Jim Gaffigan known for his observational humor and family-friendly, self-deprecating style.
-
E.
The Mecca of Bodybuilding
The Mecca of Bodybuilding is the famed Gold’s Gym location in Venice, California, renowned as a historic training ground for elite bodybuilders and fitness icons.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a2a0fb08190b409ed200a9d86a6 |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 10:47 a.m.