Triple
T36109059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 Japanese Grand Prix |
E1044439
|
entity |
| Predicate | grandPrixNumberAtCircuit |
P186420
|
FINISHED |
| Object | 32nd Japanese Grand Prix at Suzuka |
—
|
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: 32nd Japanese Grand Prix at Suzuka | Statement: [2016 Japanese Grand Prix, grandPrixNumberAtCircuit, 32nd Japanese Grand Prix at Suzuka]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: grandPrixNumberAtCircuit Context triple: [2016 Japanese Grand Prix, grandPrixNumberAtCircuit, 32nd Japanese Grand Prix at Suzuka]
-
A.
grandPrixNumberInHistory
Indicates the ordinal position of a particular Grand Prix within the overall historical sequence of all Grand Prix events.
-
B.
GrandPrixCircuitTurns
Indicates the number or configuration of turns present in a Grand Prix racing circuit.
-
C.
grandPrixEventNumberInSeason
Indicates the ordinal position of a specific Grand Prix event within the sequence of all Grand Prix events held in a given season.
-
D.
grandPrixName
Indicates the official name assigned to a particular Grand Prix event.
-
E.
GrandPrixCircuitLengthKm
Indicates the total length, measured in kilometers, of a Grand Prix racing circuit.
- F. None of above. chosen
Provenance (4 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_69f76e344a4c8190af3858c6d78ba88f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7cec454a88190a9f3bbee2b856636 |
completed | May 3, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f7c8977c288190997a892ec5f756ed |
completed | May 3, 2026, 10:13 p.m. |
| PDg | Predicate description generation | batch_69f7cec398ac819081c954a993c323ee |
completed | May 3, 2026, 10:40 p.m. |
Created at: May 3, 2026, 4:08 p.m.