Triple
T36168881
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oldsmobile dealership |
E1046092
|
entity |
| Predicate | brandOfDealership |
P185382
|
FINISHED |
| Object | Oldsmobile |
—
|
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: Oldsmobile | Statement: [Oldsmobile dealership, brandOfDealership, Oldsmobile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: brandOfDealership Context triple: [Oldsmobile dealership, brandOfDealership, Oldsmobile]
-
A.
catalogBrand
Indicates that a brand is associated with, or offered within, a particular catalog.
-
B.
brandNumber
Indicates the identifying number or code assigned to a particular brand within a system or dataset.
-
C.
engineBrand
Indicates that one entity is the brand or manufacturer of the engine used by another entity.
-
D.
vehicleBrandAssociated
Indicates that there is an association or linkage between a vehicle and a particular brand.
-
E.
cargoBrand
Indicates that a particular brand is associated with or carried as cargo in a given transport or shipment context.
- 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_69f76e396bc88190b99d221bff9be27a |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be520f148190ba200bf3dbf40656 |
completed | May 3, 2026, 9:29 p.m. |
Created at: May 3, 2026, 4:08 p.m.