Triple
T18044898
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Justify |
E431745
|
entity |
| Predicate | trainedBy |
P3665
|
FINISHED |
| Object | Bob Baffert |
—
|
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: Bob Baffert | Statement: [Justify, trainedBy, Bob Baffert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bob Baffert Context triple: [Justify, trainedBy, Bob Baffert]
-
A.
Bob Baffert
chosen
Bob Baffert is a prominent American Thoroughbred racehorse trainer known for conditioning multiple champions and winning numerous Triple Crown and Breeders’ Cup races.
-
B.
Bode Baffert
Bode Baffert is the son of renowned American Thoroughbred racehorse trainer Bob Baffert.
-
C.
Bill Mott
Bill Mott is a Hall of Fame American Thoroughbred racehorse trainer best known for conditioning champions such as the legendary racehorse Cigar.
-
D.
Jill Baffert
Jill Baffert is the wife of prominent American Thoroughbred racehorse trainer Bob Baffert and is known for her involvement in the horse racing community.
-
E.
Ogden Phipps
Ogden Phipps was a prominent American financier, art collector, and influential Thoroughbred racehorse owner and breeder.
- 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_69d8b906482481908183315b9ecf9994 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4bff13f488190993445769551c9c2 |
completed | April 19, 2026, 11:43 a.m. |
Created at: April 10, 2026, 10:25 a.m.