Triple
T24536066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet automotive industry |
E606952
|
entity |
| Predicate | mainOffRoadVehicleProducer |
P101552
|
FINISHED |
| Object | UAZ |
—
|
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: UAZ | Statement: [Soviet automotive industry, mainOffRoadVehicleProducer, UAZ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainOffRoadVehicleProducer Context triple: [Soviet automotive industry, mainOffRoadVehicleProducer, UAZ]
-
A.
bikeManufacturer
Indicates that one entity is the manufacturer or producer of a bicycle associated with another entity.
-
B.
producedVehicle
chosen
Indicates that one entity manufactured or created a particular vehicle.
-
C.
motorcycleBrand
Indicates that one entity is a brand or manufacturer of the motorcycle represented by the other entity.
-
D.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
-
E.
motoOf
Indicates that something is the motto associated with a particular entity (such as an organization, place, or group).
- 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_69e2c4c90c848190b23c4303620dcaaf |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6b0ca8081908d931aec560eae56 |
completed | April 30, 2026, 12:47 a.m. |
Created at: April 18, 2026, 2:26 a.m.