Triple
T15842843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2007 Japanese Grand Prix |
E384138
|
entity |
| Predicate | safetyCarStart |
P120083
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [2007 Japanese Grand Prix, safetyCarStart, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCarStart Context triple: [2007 Japanese Grand Prix, safetyCarStart, yes]
-
A.
safetyCarPossible
Indicates that conditions are such that deploying a safety car is a valid or allowable option.
-
B.
safetyCarFrequency
Indicates how often a safety car is deployed or appears within a given context or time frame.
-
C.
safetyCarPeriods
Indicates periods during an event when a safety car is deployed, affecting normal progression or conditions.
-
D.
safetyCarSupplier
Indicates that one entity serves as the provider or manufacturer of safety cars for another entity or event.
-
E.
safetyCarLapRecordHolder
Indicates that one entity holds the record for the most notable or fastest performance during a lap completed under safety car conditions in a race.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142e88ff08190a1035269e8fdaa6a |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
| PDg | Predicate description generation | batch_69e007869ae481909473ee220a7ccdb5 |
completed | April 15, 2026, 9:47 p.m. |
Created at: April 10, 2026, 4:50 a.m.