Triple
T35164042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F4 UAE |
E1015344
|
entity |
| Predicate | ageProfileOfDrivers |
P182351
|
FINISHED |
| Object | teenage drivers |
—
|
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: teenage drivers | Statement: [F4 UAE, ageProfileOfDrivers, teenage drivers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageProfileOfDrivers Context triple: [F4 UAE, ageProfileOfDrivers, teenage drivers]
-
A.
typicalDriverRatings
Indicates the usual or average ratings that drivers receive, representing a typical evaluation of their performance.
-
B.
hasAIDrivers
Indicates that an entity possesses or is equipped with AI-based drivers that control or operate it.
-
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.
featuresDrivers
Indicates that something includes or highlights specific drivers as notable components or participants.
-
E.
allowsCupDrivers
Indicates that one entity grants permission or authorization for Cup drivers to participate in or make use of another entity.
- F. None of above. chosen
Provenance (4 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_69f76ddbfde081908bffc91572368289 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78d2ebc2881909d76e154524ec6e6 |
completed | May 3, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69f78b9106008190930b3b3675b737d6 |
completed | May 3, 2026, 5:53 p.m. |
| PDg | Predicate description generation | batch_69f78c337cec8190bfdab225a3cc96db |
completed | May 3, 2026, 5:56 p.m. |
Created at: May 3, 2026, 4:02 p.m.