Triple
T18289118
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deuce and a Quarter |
E438060
|
entity |
| Predicate | associatedWithVehicleSegment |
P131201
|
FINISHED |
| Object | luxury car |
—
|
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: luxury car | Statement: [Deuce and a Quarter, associatedWithVehicleSegment, luxury car]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithVehicleSegment Context triple: [Deuce and a Quarter, associatedWithVehicleSegment, luxury car]
-
A.
associatedWithDriver
Indicates that one entity has a connection or relationship with a specific driver, such as being linked, assigned, or otherwise related to that driver.
-
B.
alsoAssociatedWithDriver
Indicates that an entity has an additional or secondary association with a specified driver, beyond any primary or previously stated driver relationship.
-
C.
belongsToVehicle
Indicates that something is a part of, associated with, or owned by a particular vehicle.
-
D.
mobilitySegment
Indicates a distinct portion or phase within a broader movement or travel activity, treated as a separate unit of mobility.
-
E.
relatedVehicle
Indicates that there exists an associated or connected vehicle that has a relevant relationship to the primary 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500fd65888190afdbb29dc60066af |
completed | April 19, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
| PDg | Predicate description generation | batch_69e451a0ba208190a5fe92832a8f7a49 |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 10:35 a.m.