Triple
T33315200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Circuito de Jerez-Ángel Nieto |
E852996
|
entity |
| Predicate | firstSpanishGPAtCircuit |
P126981
|
FINISHED |
| Object | 1987 |
—
|
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: 1987 | Statement: [Circuito de Jerez-Ángel Nieto, firstSpanishGPAtCircuit, 1987]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSpanishGPAtCircuit Context triple: [Circuito de Jerez-Ángel Nieto, firstSpanishGPAtCircuit, 1987]
-
A.
firstRaceAtCircuit
chosen
Indicates that the referenced race is the first race ever held at the specified circuit.
-
B.
MonacoGrandPrixLocation
Indicates that a specified location is the venue where the Monaco Grand Prix takes place.
-
C.
F1BrazilianGPRegularVenueFrom
Indicates that a location has regularly served as the venue for the Brazilian Formula 1 Grand Prix starting from a specified time.
-
D.
firstFormulaOneGrandPrix
Indicates the event at which an entity made its debut participation in a Formula One Grand Prix.
-
E.
hostedSanMarinoGrandPrixTo
Indicates that the subject served as the host location or organizer for the San Marino Grand Prix event for the object (e.g., a specific year or edition).
- 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_69f349679fd8819093b9b40e989440e3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:33 a.m.