Triple
T6350416
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volvo Group |
E142854
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object | Renault Trucks |
E587334
|
NE FINISHED |
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: Renault Trucks | Statement: [Volvo Group, subsidiary, Renault Trucks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Renault Trucks Context triple: [Volvo Group, subsidiary, Renault Trucks]
-
A.
Renault Trucks
chosen
Renault Trucks is a French commercial vehicle manufacturer known for producing a wide range of trucks and heavy-duty vehicles for distribution, construction, and long-haul transport.
-
B.
Traton
Traton is a commercial vehicle manufacturer and holding company that oversees brands like MAN and Scania within the Volkswagen Group.
-
C.
Iveco
Iveco is an Italian multinational company that designs and manufactures commercial vehicles, military vehicles, and diesel engines.
-
D.
Renault Trafic
The Renault Trafic is a light commercial van produced by French automaker Renault, widely used in Europe for cargo and passenger transport.
-
E.
Systra
Systra is a global engineering and consulting firm specializing in mass transit and rail infrastructure projects.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c008d6dcbc8190aa1c2f1fd8916b42 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c067bcec2c8190bb383605847b0f0b |
completed | March 22, 2026, 10:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62d52cbd881908ac36eca108f3194 |
completed | March 27, 2026, 7:10 a.m. |
Created at: March 22, 2026, 4:31 p.m.