Triple
T28991109
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2022 São Paulo Grand Prix qualifying |
E736026
|
entity |
| Predicate | safetyCarUsageDuringSession |
P121301
|
FINISHED |
| Object | false |
—
|
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: false | Statement: [2022 São Paulo Grand Prix qualifying, safetyCarUsageDuringSession, false]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: safetyCarUsageDuringSession Context triple: [2022 São Paulo Grand Prix qualifying, safetyCarUsageDuringSession, false]
-
A.
safetyCarUsed
chosen
Indicates that a safety car was deployed and used during an event or activity.
-
B.
safetyCarPeriods
Indicates periods during an event when a safety car is deployed, affecting normal progression or conditions.
-
C.
safetyCarFrequency
Indicates how often a safety car is deployed or appears within a given context or time frame.
-
D.
safetyCarPossible
Indicates that conditions are such that deploying a safety car is a valid or allowable option.
-
E.
safetyCarLaps
Indicates the number of laps in a race that were completed under safety car conditions.
- 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_69f077eacd0481908ef0bafd74491cd0 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 9:25 a.m.