Triple
T15842989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giedo van der Garde |
E384141
|
entity |
| Predicate | hasDrivenCarNumber |
P52123
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Giedo van der Garde, hasDrivenCarNumber, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDrivenCarNumber Context triple: [Giedo van der Garde, hasDrivenCarNumber, 21]
-
A.
droveCarNumber
chosen
Indicates that a person operated or was driving a specific car identified by its number.
-
B.
hasDrivenInCategory
Indicates that an entity has previously driven or operated a vehicle within a specified driving category or classification.
-
C.
drivingExperience
Indicates the extent or history of a person's involvement in driving vehicles, typically measured by duration, frequency, or level of skill.
-
D.
hasDrivingSkill
Indicates that an entity possesses the ability or competence to operate and control a vehicle.
-
E.
droveFor
Indicates that one entity operated a vehicle on behalf of, or in service to, another entity for a certain period or purpose.
- 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_69d86da34c888190976e06c4019d415a |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e142ea3da08190a9d2d5917f84907c |
completed | April 16, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.