Triple
T6850854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Formula 2 Championship |
E158009
|
entity |
| Predicate | pitStopsMandatoryInFeatureRace |
P44365
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Formula 2 Championship, pitStopsMandatoryInFeatureRace, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pitStopsMandatoryInFeatureRace Context triple: [Formula 2 Championship, pitStopsMandatoryInFeatureRace, true]
-
A.
pitStopsRequired
chosen
Indicates that a process, journey, or operation necessitates one or more scheduled pit stops to be completed.
-
B.
safetyCarFrequency
Indicates how often a safety car is deployed or appears within a given context or time frame.
-
C.
safetyCarPossible
Indicates that conditions are such that deploying a safety car is a valid or allowable option.
-
D.
hasRacecourseFeature
Indicates that something possesses or includes a specific feature or characteristic related to a racecourse.
-
E.
hasStopFeature
Indicates that one entity possesses or is equipped with a feature that enables stopping or halting an associated process, action, or movement.
- 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_69c6882fae988190864cbba788c5ebb4 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d84c45708190918adfc028252400 |
completed | March 27, 2026, 7:19 p.m. |
| PD | Predicate disambiguation | batch_69c6d0a12834819097d7e6c0b823745e |
completed | March 27, 2026, 6:46 p.m. |
Created at: March 27, 2026, 2:20 p.m.