Triple
T3881546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James Hunt |
E92832
|
entity |
| Predicate | totalFormulaOneEntries |
P52121
|
FINISHED |
| Object | 93 |
—
|
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: 93 | Statement: [James Hunt, totalFormulaOneEntries, 93]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalFormulaOneEntries Context triple: [James Hunt, totalFormulaOneEntries, 93]
-
A.
F1LapRecordHolder
Indicates that the subject holds the fastest lap record in a Formula 1 race or at a specific Formula 1 circuit.
-
B.
heldFIAEntry
Indicates that an entity possessed or maintained an official FIA (Fédération Internationale de l'Automobile) entry status for a competition or event.
-
C.
numberOfGrandTourOverallVictories
Indicates the total count of times an entity has won the overall classification in any of cycling’s Grand Tours (Tour de France, Giro d’Italia, or Vuelta a España).
-
D.
F1LapRecordCar
Indicates the car that holds the lap record in a Formula 1 session or at a specific F1 circuit.
-
E.
F1LapRecordYear
Indicates the year in which a specific Formula 1 lap record was set.
- F. None of above. chosen
Provenance (4 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_69aed9697de0819087c2559295ff3d12 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.