Triple
T26473969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Thomas Assembly Plant |
E665975
|
entity |
| Predicate | lastVehicleProduced |
P13157
|
FINISHED |
| Object | Ford Crown Victoria |
—
|
NE NERFINISHED |
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: Ford Crown Victoria | Statement: [St. Thomas Assembly Plant, lastVehicleProduced, Ford Crown Victoria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lastVehicleProduced Context triple: [St. Thomas Assembly Plant, lastVehicleProduced, Ford Crown Victoria]
-
A.
lastModelProduced
chosen
Indicates that one entity is the most recently created or generated model associated with another entity.
-
B.
lastAppearanceYear
Indicates the calendar year in which an entity made its most recent appearance.
-
C.
latestProductionYear
Indicates the most recent year in which the entity was produced or manufactured.
-
D.
producedVehicle
Indicates that one entity manufactured or created a particular vehicle.
-
E.
yearFirstDelivered
Indicates the calendar year in which something (such as a product, service, or item) was first delivered or made available.
- 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_69ee883f80dc819090e311b022b78e02 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f612cbbd188190bf01aede80ba1db5 |
completed | May 2, 2026, 3:05 p.m. |
| PD | Predicate disambiguation | batch_69f60b89cc048190a9feb24466006be0 |
completed | May 2, 2026, 2:34 p.m. |
Created at: April 27, 2026, 12:21 a.m.