Triple
T35795358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1950 Italian Grand Prix |
E1034815
|
entity |
| Predicate | grandPrixSequenceInCountry |
P77357
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [1950 Italian Grand Prix, grandPrixSequenceInCountry, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandPrixSequenceInCountry Context triple: [1950 Italian Grand Prix, grandPrixSequenceInCountry, 21]
-
A.
previousF1FrenchGPLocation
Indicates that one location served as the venue for the immediately preceding Formula 1 French Grand Prix relative to another referenced race or event.
-
B.
homeGrandPrix
Indicates that a particular Grand Prix event is considered the home race for a given driver, team, or country.
-
C.
grandPrixName
Indicates the official name assigned to a particular Grand Prix event.
-
D.
grandPrixNumberInHistory
chosen
Indicates the ordinal position of a particular Grand Prix within the overall historical sequence of all Grand Prix events.
-
E.
F1GrandsPrixEntered
Indicates the number of Formula 1 Grand Prix events that an entity has officially entered.
- 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_69f76e169bd081909f16cd8c9ee7870c |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7c29e1b848190b945c6c6120a5330 |
completed | May 3, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f7c1b6e7a881908deb96bedb2713f4 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:06 p.m.