Triple
T35753336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian Grand Prix |
E1033373
|
entity |
| Predicate | firstF1WorldChampionshipSeason |
P102108
|
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: [Belgian Grand Prix, firstF1WorldChampionshipSeason, 1950]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstF1WorldChampionshipSeason Context triple: [Belgian Grand Prix, firstF1WorldChampionshipSeason, 1950]
-
A.
firstF1Season
Indicates the Formula 1 season in which an entity (typically a driver or team) first competed.
-
B.
firstF1GrandPrixYear
chosen
Indicates the year in which a given Formula 1 Grand Prix was first held.
-
C.
firstF1RaceHeld
Indicates that the subject is the location or venue where the first Formula 1 race was held.
-
D.
grandPrixDebutYear
Indicates the year in which an entity first participated in a Grand Prix event.
-
E.
firstUsedForFormulaOneWorldChampionship
Indicates that something (typically a circuit, track, or venue) was used for the first time in hosting a Formula One World Championship 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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_6a037ce70f54819082946dad8d380825 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a069e6c8190857b611fffb7b867 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:06 p.m.