Triple
T36988280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Air Force Blue |
E915023
|
entity |
| Predicate | primaryJockey |
—
|
GENERATED |
| Object | Ryan Moore |
—
|
UNRECOGNIZED GENERATED |
How this triple was built (1 step)
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.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryJockey Context triple: [Air Force Blue, primaryJockey, Ryan Moore]
-
A.
mostSuccessfulJockey
Indicates that the subject is the jockey with the highest level of success (e.g., most wins or top performance) in a given context or competition.
-
B.
hasJockey
chosen
Indicates that a racehorse is associated with or ridden by a particular jockey.
-
C.
hasNotableJockey
Indicates that an entity (typically a racehorse) is or was ridden by a jockey who is considered notable or distinguished.
-
D.
firstRider
Indicates that one entity is the first rider in relation to another entity, typically marking the earliest or primary participant in a riding-related context.
-
E.
winningTrainer
Indicates that the trainer is the one who achieved victory in a particular competition or event.
- F. None of above.
Provenance (1 batch)
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_69f76e8dd0408190b8b46da118ea5128 |
completed | May 3, 2026, 3:49 p.m. |
Created at: May 3, 2026, 4:14 p.m.