Triple
T19999301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fast N' Loud |
E494274
|
entity |
| Predicate | hasMainPersonOccupation |
P105981
|
FINISHED |
| Object | custom car builder |
—
|
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: custom car builder | Statement: [Fast N' Loud, hasMainPersonOccupation, custom car builder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainPersonOccupation Context triple: [Fast N' Loud, hasMainPersonOccupation, custom car builder]
-
A.
hasTypicalOccupation
Indicates that an entity commonly or characteristically works in a particular job or profession.
-
B.
holderIsOccupation
chosen
Indicates that the holder entity has the specified occupation or job role.
-
C.
hasOccupationFocus
Indicates that an entity’s occupation is primarily centered on, or specialized in, a particular field, role, or area of activity.
-
D.
endedOccupationOf
Indicates that one entity brought another entity’s occupation or control of a place or position to an end.
-
E.
hasMainPerformerOccupation
Indicates that an entity’s primary or main performer is associated with a specified occupation or professional role.
- 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_69da626b2d748190886981ea90c8b2ea |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e661a09bdc819083305b08a11c6e34 |
completed | April 20, 2026, 5:25 p.m. |
| PD | Predicate disambiguation | batch_69e537fd311881908448f2aea8b4812e |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:32 p.m.