Triple
T28991062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kevin Magnussen |
E736025
|
entity |
| Predicate | isChildOfRacingDriver |
P61371
|
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: [Kevin Magnussen, isChildOfRacingDriver, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isChildOfRacingDriver Context triple: [Kevin Magnussen, isChildOfRacingDriver, true]
-
A.
isFromRacingFamily
chosen
Indicates that an entity belongs to or originates from a family with a background or tradition in racing.
-
B.
racingDriver
Indicates that one entity is a racing driver, i.e., a person who competes in motor races as a driver.
-
C.
hasFictionalDriver
Indicates that an entity (such as a vehicle or object) is associated with a driver who is a fictional or imaginary character.
-
D.
alsoAssociatedWithDriver
Indicates that an entity has an additional or secondary association with a specified driver, beyond any primary or previously stated driver relationship.
-
E.
hasMotorsportInvolvement
Indicates that an entity is involved in motorsport, such as through participation, organization, sponsorship, or other direct association with motor racing activities.
- 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_69f65f7d3b5c8190937aaddff2879989 |
completed | May 2, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69f659d02f1c8190831758ac52bb54e4 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 28, 2026, 9:25 a.m.