Triple
T35698368
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hambach, France |
E1031504
|
entity |
| Predicate | hasVehicleModelProduced |
P140377
|
FINISHED |
| Object | Smart EQ fortwo |
—
|
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: Smart EQ fortwo | Statement: [Hambach, France, hasVehicleModelProduced, Smart EQ fortwo]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVehicleModelProduced Context triple: [Hambach, France, hasVehicleModelProduced, Smart EQ fortwo]
-
A.
vehicleModelProduced
chosen
Indicates that a particular vehicle model is manufactured or produced by a specific company or producer.
-
B.
producedVehicle
Indicates that one entity manufactured or created a particular vehicle.
-
C.
tankModelProduced
Indicates that a particular model or variant of a tank was manufactured or brought into production by some producer or manufacturer.
-
D.
modelProduced
Indicates that a particular model has generated or produced a specified output, result, or artifact.
-
E.
hasModelSeries
Indicates a relationship where an item or product is associated with a specific model series it belongs to.
- 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_69f76e0d393c8190b6303c64408736db |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.