Triple
T24536042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soviet automotive industry |
E606952
|
entity |
| Predicate | majorManufacturer |
P51141
|
FINISHED |
| Object | GAZ |
—
|
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: GAZ | Statement: [Soviet automotive industry, majorManufacturer, GAZ]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorManufacturer Context triple: [Soviet automotive industry, majorManufacturer, GAZ]
-
A.
notableManufacturer
chosen
Indicates that an entity is a well-known or prominent producer or maker of another entity.
-
B.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
-
C.
majorVendor
Indicates that one entity serves as a primary or leading supplier of goods or services to another entity.
-
D.
manufacturerStatus
Indicates the current operational or business condition of a manufacturer in relation to the product or agreement in question.
-
E.
manufacturerClass
Indicates that an entity belongs to, or is categorized within, a particular class or type of manufacturer.
- 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.