Triple
T16180294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Type S |
E392665
|
entity |
| Predicate | engineTypeExamples |
P50109
|
FINISHED |
| Object | turbocharged four-cylinder 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 four-cylinder engines | Statement: [Type S, engineTypeExamples, turbocharged four-cylinder engines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: engineTypeExamples Context triple: [Type S, engineTypeExamples, turbocharged four-cylinder engines]
-
A.
engineTypeUsed
Indicates that a particular type of engine is employed or utilized in relation to a specified entity or system.
-
B.
notableEngineType
Indicates that an entity is particularly recognized for using or being associated with a specific type of engine.
-
C.
engineUsedIn
Indicates that a particular engine is utilized as a component or power source within a specified system, device, or application.
-
D.
testedEngineType
Indicates that an engine of a specified type has been subjected to a test or evaluation.
-
E.
engineClass
chosen
Indicates the classification or type category assigned to an engine within a given system or context.
- 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_69d87f1e49ac8190a311b54d32990576 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e2205c92b48190b7125dbbcff3662e |
completed | April 17, 2026, 11:58 a.m. |
| PD | Predicate disambiguation | batch_69e219d642708190ba31a90dce76a210 |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:02 a.m.