Triple
T11893655
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Autódromo José Carlos Pace |
E282980
|
entity |
| Predicate | F1LapRecordTime |
P77656
|
FINISHED |
| Object | 1:10.540 |
—
|
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: 1:10.540 | Statement: [Autódromo José Carlos Pace, F1LapRecordTime, 1:10.540]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: F1LapRecordTime Context triple: [Autódromo José Carlos Pace, F1LapRecordTime, 1:10.540]
-
A.
F1LapRecordHolder
Indicates that the subject holds the fastest lap record in a Formula 1 race or at a specific Formula 1 circuit.
-
B.
F1LapRecordCar
Indicates the car that holds the lap record in a Formula 1 session or at a specific F1 circuit.
-
C.
fastestLapTime
chosen
Indicates the shortest recorded time an entity achieved to complete a single lap in a given context or event.
-
D.
fastestLapLapNumber
Indicates the specific lap number on which the fastest lap was achieved in a race.
-
E.
F1LapRecordCategory
Indicates that an entity holds or pertains to a specific category of Formula 1 lap record (such as overall, qualifying, or race lap records).
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8dd1172988190a2c13d37220f2f93 |
completed | April 10, 2026, 11:20 a.m. |
| PD | Predicate disambiguation | batch_69d8bb2fca4481909893f3428b0871ac |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.