Triple
T633991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bowling Green Assembly Plant |
E15981
|
entity |
| Predicate | hasAssemblyLineFor |
P17333
|
FINISHED |
| Object | front mid-engine sports cars |
—
|
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 mid-engine sports cars | Statement: [Bowling Green Assembly Plant, hasAssemblyLineFor, front mid-engine sports cars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssemblyLineFor Context triple: [Bowling Green Assembly Plant, hasAssemblyLineFor, front mid-engine sports cars]
-
A.
assemblyMeetsEvery
Indicates that an assembly convenes or holds meetings at every specified time, place, or condition in the given context.
-
B.
hasPart
Indicates that one entity is a component, segment, or constituent part of another entity.
-
C.
isBuiltFor
Indicates that one entity is specifically designed, intended, or optimized to serve, support, or accommodate another entity or purpose.
-
D.
usedInProductLine
Indicates that something (such as a component, material, or feature) is utilized within a particular product line.
-
E.
isLinedWith
Indicates that one object or surface is covered, edged, or internally coated along its length or area with another material or layer.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ec3b6488190aa0dce216c089a2e |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d030c648190ba1a02301b45f694 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.