Triple
T38464295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pura |
E912524
|
entity |
| Predicate | vehicleClassInCTR |
P190925
|
FINISHED |
| Object | lightweight |
—
|
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: lightweight | Statement: [Pura, vehicleClassInCTR, lightweight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vehicleClassInCTR Context triple: [Pura, vehicleClassInCTR, lightweight]
-
A.
vehicleClassDriven
Indicates that an entity drives or operates a vehicle belonging to a particular vehicle class or category.
-
B.
vehicleType
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
C.
mainVehicleClass
Indicates the primary category or type of vehicle to which an entity chiefly belongs.
-
D.
vehicleRegistrationCategory
Indicates the classification or type of registration assigned to a vehicle under a specific regulatory or administrative scheme.
-
E.
intendedVehicleClass
Indicates that one entity is designed or specified to be used with, or is appropriate for, a particular class or category of vehicle.
- 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_69f76e861d8c81908559031dc66e3c15 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd34596288190b8e34a7a20b4c0db |
completed | May 7, 2026, 6 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
| PDg | Predicate description generation | batch_69fcd31227708190a7df213597e66ca8 |
completed | May 7, 2026, 5:59 p.m. |
Created at: May 3, 2026, 4:31 p.m.