Triple
T37401058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1959 United States Grand Prix |
E928995
|
entity |
| Predicate | worldDriversChampionCountry |
P109361
|
FINISHED |
| Object | Australia |
—
|
NE NERFINISHED |
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: Australia | Statement: [1959 United States Grand Prix, worldDriversChampionCountry, Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: worldDriversChampionCountry Context triple: [1959 United States Grand Prix, worldDriversChampionCountry, Australia]
-
A.
worldDriversChampionNationality
chosen
Indicates the nationality associated with a given world drivers champion.
-
B.
coDriversChampionNationality
Indicates the nationality of the co-driver who won the championship.
-
C.
driversChampionships
Indicates the number of drivers’ championship titles an entity has won or is associated with.
-
D.
polePositionDriverNationality
Indicates the nationality associated with the driver who secured pole position in a race.
-
E.
driversChampionWins
Indicates the number of championship titles won by a particular driver.
- 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_69f76ebbf79c8190b85bbcf3a6be57e4 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 3, 2026, 4:16 p.m.