Triple
T15847754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EQA 350 4MATIC |
E384256
|
entity |
| Predicate | electricVehicleType |
P1776
|
FINISHED |
| Object | battery electric SUV |
—
|
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: battery electric SUV | Statement: [EQA 350 4MATIC, electricVehicleType, battery electric SUV]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electricVehicleType Context triple: [EQA 350 4MATIC, electricVehicleType, battery electric SUV]
-
A.
vehicleType
chosen
Indicates the specific kind or category of vehicle associated with an entity (e.g., car, bus, bicycle).
-
B.
electricMotorType
Indicates the specific kind or category of electric motor associated with an entity.
-
C.
EVAType
Indicates the type or category of an extravehicular activity (EVA) associated with an entity, specifying what kind of EVA operation or event it represents.
-
D.
vehicleFamily
Indicates that two vehicles belong to the same family or category based on shared design, platform, or lineage.
-
E.
vehicleTypeFocus
Indicates that the relationship or action specifically concerns or emphasizes a particular type or category of vehicle.
- 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_69d86da422088190aac39e32e6c68429 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e14ca96c588190922b1f7556dd08cf |
completed | April 16, 2026, 8:55 p.m. |
| PD | Predicate disambiguation | batch_69e005434ed88190baf11c169da3cf29 |
completed | April 15, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:50 a.m.