Triple
T12372359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chris Buescher |
E295033
|
entity |
| Predicate | driverCategory |
P69218
|
FINISHED |
| Object | professional |
—
|
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: professional | Statement: [Chris Buescher, driverCategory, professional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: driverCategory Context triple: [Chris Buescher, driverCategory, professional]
-
A.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
hasDriverCategory
chosen
Indicates that an entity (such as a vehicle or driving role) is associated with a specific driver category or license class.
-
C.
vehicleRegistrationCategory
Indicates the classification or type of registration assigned to a vehicle under a specific regulatory or administrative scheme.
-
D.
coachType
Indicates the specific category or role of a coach associated with an entity (e.g., head coach, assistant coach, position coach).
-
E.
driveType
Indicates the type or configuration of the drive mechanism used to power or propel an entity.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:54 p.m.