Triple
T27144197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galway Plate |
E681896
|
entity |
| Predicate | hasHorseType |
P77266
|
FINISHED |
| Object | thoroughbred |
—
|
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: thoroughbred | Statement: [Galway Plate, hasHorseType, thoroughbred]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHorseType Context triple: [Galway Plate, hasHorseType, thoroughbred]
-
A.
usesHorseType
Indicates that one entity employs, relies on, or operates using a specific type or category of horse.
-
B.
hasRacehorseCharacter
Indicates that one entity possesses the traits, qualities, or behavioral characteristics associated with a racehorse in relation to another entity or context.
-
C.
horseBreed
chosen
Indicates that one entity is a specific breed of the horse represented by the other entity.
-
D.
featuresHorse
Indicates that something includes, presents, or prominently involves a horse as a central element or subject.
-
E.
typicalAttributesOfHorse
Indicates the standard or commonly expected characteristics or properties associated with a horse.
- 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_69eefacca3888190b67238d380e8f28b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 9:10 a.m.