Triple
T2199107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ford Mustang Bullitt edition |
E50446
|
entity |
| Predicate | hasEngineLayout |
P19520
|
FINISHED |
| Object | front-engine |
—
|
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: front-engine | Statement: [Ford Mustang Bullitt edition, hasEngineLayout, front-engine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEngineLayout Context triple: [Ford Mustang Bullitt edition, hasEngineLayout, front-engine]
-
A.
vehicleLayout
Indicates how the components or seating within a vehicle are arranged or configured relative to each other.
-
B.
hasLayout
Indicates that one entity defines or is associated with the structural arrangement or organization (layout) of another entity.
-
C.
propulsionLayout
chosen
Indicates how propulsion components are arranged or configured relative to each other within a system.
-
D.
testedEngineType
Indicates that an engine of a specified type has been subjected to a test or evaluation.
-
E.
hasWingConfiguration
Indicates how an entity’s wings are arranged, structured, or configured relative to its body or to each other.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf7b65cc8190bcc5a5c52b90f33b |
completed | March 7, 2026, 6:02 a.m. |
| PD | Predicate disambiguation | batch_69abbda706f4819094de73e1d1d1f539 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.