Triple
T136216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saab Automobile |
E2751
|
entity |
| Predicate | notableEngineType |
P4856
|
FINISHED |
| Object | turbocharged inline-four engines |
—
|
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: turbocharged inline-four engines | Statement: [Saab Automobile, notableEngineType, turbocharged inline-four engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableEngineType Context triple: [Saab Automobile, notableEngineType, turbocharged inline-four engines]
-
A.
typicalEngine
Indicates that an entity is the standard or commonly used engine for another entity (such as a vehicle, device, or system).
-
B.
notableSystem
Indicates that a system is recognized as significant, prominent, or noteworthy in a particular context or domain.
-
C.
availableEngineDisplacement
Indicates the range or specific values of engine displacement that are offered or applicable for a given entity.
-
D.
numberOfEngines
Indicates the quantity of engines associated with or used by an entity.
-
E.
notableTrain
Indicates that there is a train or rail service associated with the subject that is considered notable or significant in some way.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257a4edf081908c494c8370c76b9a |
completed | Feb. 28, 2026, 2:49 a.m. |
| PD | Predicate disambiguation | batch_69a25651b9048190a6277b7fec98c1ea |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c80c5c81908b31cc513fd27566 |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.