Triple
T6185423
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grand National |
E138042
|
entity |
| Predicate | typicalNumberOfRunners |
P27342
|
FINISHED |
| Object | up to 40 |
—
|
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: up to 40 | Statement: [Grand National, typicalNumberOfRunners, up to 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfRunners Context triple: [Grand National, typicalNumberOfRunners, up to 40]
-
A.
typicalNumberOfAthletes
chosen
Indicates the usual or average number of athletes associated with or participating in a given context, event, or entity.
-
B.
typicalRaceDistanceLaps
Indicates the usual number of laps that constitute the standard race distance for a given racing event or category.
-
C.
scoringRunnersCount
Indicates the number of runners who successfully score (e.g., reach home plate or equivalent scoring position) as a result of a particular play or action.
-
D.
numberOfRaces
Indicates the total count of races associated with a given entity or event.
-
E.
numberOfRiders
Indicates the total count of riders associated with a given entity or event.
- 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_69c008a8fd408190b7ec6e42934974a6 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062150fc48190877240abe6b6c636 |
completed | March 22, 2026, 9:41 p.m. |
| PD | Predicate disambiguation | batch_69c055fa0a808190bda37832e3ac150c |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:19 p.m.