Triple
T35752912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1938 European Championship |
E1033362
|
entity |
| Predicate | championDriverNationality |
P109361
|
FINISHED |
| Object | Italian |
—
|
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: Italian | Statement: [1938 European Championship, championDriverNationality, Italian]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championDriverNationality Context triple: [1938 European Championship, championDriverNationality, Italian]
-
A.
coDriversChampionNationality
Indicates the nationality of the co-driver who won the championship.
-
B.
worldDriversChampionNationality
chosen
Indicates the nationality associated with a given world drivers champion.
-
C.
polePositionDriverNationality
Indicates the nationality associated with the driver who secured pole position in a race.
-
D.
championTeamDrivers
Indicates that the specified drivers were the official championship-winning drivers for the given team in a particular competition or season.
-
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_69f76e1262f48190a313318665acc189 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fbaebc8f2c8190b94f1b4a3ec92e8c |
completed | May 6, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69fbadf1e6008190a71bbd196ba06844 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:06 p.m.