Triple
T34918355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freehold Raceway |
E1007067
|
entity |
| Predicate | racingBreed |
P77266
|
FINISHED |
| Object | Standardbred |
—
|
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: Standardbred | Statement: [Freehold Raceway, racingBreed, Standardbred]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racingBreed Context triple: [Freehold Raceway, racingBreed, Standardbred]
-
A.
horseBreed
chosen
Indicates that one entity is a specific breed of the horse represented by the other entity.
-
B.
raceTypeDetail
Indicates the specific category or classification of a race, providing detailed information about the type of race involved in the relationship.
-
C.
bullSportType
Indicates that a bull is associated with a particular type of sport or sporting activity.
-
D.
bearerRace
Indicates the racial or ethnic classification associated with the bearer in the relationship.
-
E.
raceTypeStrength
Indicates the degree or category of physical or competitive strength associated with a particular race type in the relationship.
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f782c98fa08190870b68de2c1ff26a |
completed | May 3, 2026, 5:15 p.m. |
| PD | Predicate disambiguation | batch_69f781020cc4819088c40cb8589504e4 |
completed | May 3, 2026, 5:08 p.m. |
Created at: May 3, 2026, 4 p.m.