Triple
T28343054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buddh International Circuit |
E717867
|
entity |
| Predicate | F1NumberOfGrandsPrixHosted |
P120096
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Buddh International Circuit, F1NumberOfGrandsPrixHosted, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: F1NumberOfGrandsPrixHosted Context triple: [Buddh International Circuit, F1NumberOfGrandsPrixHosted, 3]
-
A.
grandPrixNumberInHistory
Indicates the ordinal position of a particular Grand Prix within the overall historical sequence of all Grand Prix events.
-
B.
F1GrandsPrixEntered
chosen
Indicates the number of Formula 1 Grand Prix events that an entity has officially entered.
-
C.
numberOfF1WorldChampionships
Indicates the number of Formula 1 World Championship titles that an entity has won.
-
D.
grandPrixRaceWins
Indicates the number of Grand Prix races that an entity has won.
-
E.
formerF1Venue
Indicates that a location previously hosted Formula 1 races but is no longer an active venue for the championship.
- 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_69eff6eb30388190b898b96c4be6f49d |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f64c04ac408190bab8dfadcc002deb |
completed | May 2, 2026, 7:09 p.m. |
| PD | Predicate disambiguation | batch_69f641e2f1708190b45b48d6a43c51d2 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 28, 2026, 12:41 a.m.