Triple
T4380934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monaco Grand Prix |
E99126
|
entity |
| Predicate | firstFormulaOneWorldChampionshipRace |
P54565
|
FINISHED |
| Object | 1950 |
—
|
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: 1950 | Statement: [Monaco Grand Prix, firstFormulaOneWorldChampionshipRace, 1950]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstFormulaOneWorldChampionshipRace Context triple: [Monaco Grand Prix, firstFormulaOneWorldChampionshipRace, 1950]
-
A.
firstFormulaOneGrandPrix
chosen
Indicates the event at which an entity made its debut participation in a Formula One Grand Prix.
-
B.
totalFormulaOneStarts
Indicates the total number of times an entity has started in Formula One races.
-
C.
firstFormulaOneTeam
Indicates the Formula One team for which an entity (typically a driver) first competed.
-
D.
totalFormulaOneWins
Indicates the total number of Formula One race victories achieved by a given driver, team, or other relevant entity.
-
E.
totalFormulaOneEntries
Indicates the total number of times an entity has participated in Formula One events or races.
- 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_69b3454ea8f48190a49c2436624d6ef6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b35243036481909fb0a001c3cb1ff2 |
completed | March 12, 2026, 11:54 p.m. |
| PD | Predicate disambiguation | batch_69b34f557fe8819085032bf7f0cea5dc |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:18 p.m.