Triple
T24536059
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet automotive industry |
E606952
|
entity |
| Predicate | mainPassengerCarProducer |
P66170
|
FINISHED |
| Object | AvtoVAZ |
—
|
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: AvtoVAZ | Statement: [Soviet automotive industry, mainPassengerCarProducer, AvtoVAZ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainPassengerCarProducer Context triple: [Soviet automotive industry, mainPassengerCarProducer, AvtoVAZ]
-
A.
usesPassengerCars
Indicates that an entity operates or employs passenger cars as part of its activities or services.
-
B.
producedVehicle
Indicates that one entity manufactured or created a particular vehicle.
-
C.
numberOfPassengerCars
Indicates the total count of passenger cars associated with or contained in a given entity or context.
-
D.
carManufacturer
chosen
Indicates that one entity is the company that produces or manufactures the car represented by the other entity.
-
E.
enteredAutomobileProduction
Indicates that an entity began manufacturing automobiles as a commercial or industrial activity.
- 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.