Triple
T10797790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1929 Schneider Trophy |
E254755
|
entity |
| Predicate | winningAverageSpeed |
P12248
|
FINISHED |
| Object | 528.89 km/h |
—
|
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: 528.89 km/h | Statement: [1929 Schneider Trophy, winningAverageSpeed, 528.89 km/h]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningAverageSpeed Context triple: [1929 Schneider Trophy, winningAverageSpeed, 528.89 km/h]
-
A.
fastestLapTime
Indicates the shortest recorded time an entity achieved to complete a single lap in a given context or event.
-
B.
hasAverageSurfaceSpeed
Indicates the typical or mean speed at which something moves across a surface over a given period or distance.
-
C.
speedAchieved
chosen
Indicates that a particular speed has been reached or attained by an entity during an event or action.
-
D.
raceWon
Indicates that one participant has achieved victory in a race or competitive event over others.
-
E.
winnerLaps
Indicates that one participant completed more laps than another, thereby winning based on lap count.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d73333dc4081909faa40c10bce2735 |
completed | April 9, 2026, 5:03 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:17 p.m.