Triple
T27416634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opel Olympia |
E692911
|
entity |
| Predicate | manufacturerOwnershipDuringProduction |
P22323
|
FINISHED |
| Object | General Motors |
—
|
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: General Motors | Statement: [Opel Olympia, manufacturerOwnershipDuringProduction, General Motors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: manufacturerOwnershipDuringProduction Context triple: [Opel Olympia, manufacturerOwnershipDuringProduction, General Motors]
-
A.
ownerOrManufacturer
Indicates that the related entity either owns the item or is the entity that manufactured it.
-
B.
formerManufacturer
Indicates that an entity previously manufactured another entity but no longer does so.
-
C.
parentCompanyDuringProduction
chosen
Indicates that one company served as the parent company of another during the time a particular production or project was being made.
-
D.
manufacturerType
Indicates the classification or category of a manufacturer based on its role, characteristics, or production type.
-
E.
hasManufacturerHistory
Indicates that there exists a record of past and/or current manufacturers associated with an entity, capturing changes or continuity in who produced it over time.
- 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_69ef5208617081908f731d312e0fd1bc |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f62d1a8c948190ab8629e1349a156f |
completed | May 2, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69f623aaf40081909f947431424a1d55 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 12:34 p.m.