Triple
T13476992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ayrton Senna |
E318274
|
entity |
| Predicate | F1PolePositions |
P57362
|
FINISHED |
| Object | 65 |
—
|
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: 65 | Statement: [Ayrton Senna, F1PolePositions, 65]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: F1PolePositions Context triple: [Ayrton Senna, F1PolePositions, 65]
-
A.
totalPolePositions
chosen
Indicates the total number of times an entity has achieved pole position in qualifying or starting order across all relevant events.
-
B.
firstPolePositionDriver
Indicates the driver who achieved the very first pole position in a given racing event or series.
-
C.
polePositionDriverNationality
Indicates the nationality associated with the driver who secured pole position in a race.
-
D.
totalFormulaOnePodiums
Indicates the total number of times an entity has finished on the podium (top three positions) in Formula One races.
-
E.
polePositions
Indicates that one entity holds the pole position (starting first) relative to another entity in a competitive event, such as a race.
- 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_69d806b6bfec819089222715b2e86c8e |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf2551b48190a074fd256791742d |
completed | April 12, 2026, 2:41 p.m. |
| PD | Predicate disambiguation | batch_69dbadfddefc81909ef7fde23b181b5c |
completed | April 12, 2026, 2:36 p.m. |
Created at: April 9, 2026, 9:42 p.m.