Triple
T15842857
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 Japanese Grand Prix |
E384138
|
entity |
| Predicate | firstJapaneseGPAtFujiInF1ModernEra |
P56267
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [2007 Japanese Grand Prix, firstJapaneseGPAtFujiInF1ModernEra, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstJapaneseGPAtFujiInF1ModernEra Context triple: [2007 Japanese Grand Prix, firstJapaneseGPAtFujiInF1ModernEra, yes]
-
A.
F1BrazilianGPRegularVenueFrom
Indicates that a location has regularly served as the venue for the Brazilian Formula 1 Grand Prix starting from a specified time.
-
B.
firstFormulaOneGrandPrix
Indicates the event at which an entity made its debut participation in a Formula One Grand Prix.
-
C.
GrandPrixTitle
Indicates that an entity has won a championship or overall title in a Grand Prix competition or series.
-
D.
firstFerrariWorldTitleSeason
Indicates the season in which an entity (typically a driver or team) won their first world championship title with Ferrari.
-
E.
firstF1RaceInRegion
chosen
Indicates that a given Formula 1 race is the first F1 race ever held within a specified geographic region.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.