Triple
T19917522
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Phipps family |
E478702
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object | Ogden Phipps |
—
|
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: Ogden Phipps | Statement: [Phipps family, hasMember, Ogden Phipps]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ogden Phipps Context triple: [Phipps family, hasMember, Ogden Phipps]
-
A.
Ogden Phipps
chosen
Ogden Phipps was a prominent American financier, art collector, and influential Thoroughbred racehorse owner and breeder.
-
B.
Bill Mott
Bill Mott is a Hall of Fame American Thoroughbred racehorse trainer best known for conditioning champions such as the legendary racehorse Cigar.
-
C.
Bode Baffert
Bode Baffert is the son of renowned American Thoroughbred racehorse trainer Bob Baffert.
-
D.
Bob Baffert
Bob Baffert is a prominent American Thoroughbred racehorse trainer known for conditioning multiple champions and winning numerous Triple Crown and Breeders’ Cup races.
-
E.
Gary Stevens (jockey)
Gary Stevens is a Hall of Fame American jockey and horse racing analyst renowned for winning multiple Kentucky Derbies, Preakness Stakes, and Breeders’ Cup races over a decades-long career.
- 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65995bd60819097cfad003dd29731 |
completed | April 20, 2026, 4:51 p.m. |
Created at: April 10, 2026, 1:53 p.m.