Triple
T18319120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mickael Barzalona |
E438822
|
entity |
| Predicate | typeOfJockey |
P51007
|
FINISHED |
| Object | flat racing jockey |
—
|
LITERAL 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: flat racing jockey | Statement: [Mickael Barzalona, typeOfJockey, flat racing jockey]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfJockey Context triple: [Mickael Barzalona, typeOfJockey, flat racing jockey]
-
A.
hasNotableJockey
Indicates that an entity (typically a racehorse) is or was ridden by a jockey who is considered notable or distinguished.
-
B.
notableRiderType
chosen
Indicates that an entity is notably associated with a particular type or category of rider (e.g., cyclist, jockey, driver).
-
C.
riderType
Indicates the category or role of a rider in relation to a ride, transport service, or vehicle (e.g., passenger, driver, courier).
-
D.
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.
-
E.
raceTypeWon
Indicates the specific type or category of race that an entity has won.
- F. None of above.
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_69d8b916a2d081909e249e4902f6aad9 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50aa4d3308190883714e1ef6a1d84 |
completed | April 19, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69e44fe4ee10819086b4142444fca1f5 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.