Triple
T6350412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volvo Group |
E142854
|
entity |
| Predicate | subsidiary |
P258
|
FINISHED |
| Object |
Volvo Trucks
Volvo Trucks is a leading global manufacturer of heavy-duty commercial vehicles known for their safety, durability, and advanced engineering.
|
E142854
|
NE FINISHED |
How this triple was built (4 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: Volvo Trucks | Statement: [Volvo Group, subsidiary, Volvo Trucks]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volvo Trucks Context triple: [Volvo Group, subsidiary, Volvo Trucks]
-
A.
Volvo Group
Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
-
B.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
-
C.
Scania
Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
-
D.
Daimler Truck AG
Daimler Truck AG is a leading global commercial vehicle manufacturer specializing in trucks and buses, formed as an independent company after its separation from the former Daimler AG.
-
E.
PACCAR
PACCAR is a major American manufacturer of commercial trucks and related heavy-duty vehicles headquartered in Bellevue, Washington.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Volvo Trucks Triple: [Volvo Group, subsidiary, Volvo Trucks]
Generated description
Volvo Trucks is a leading global manufacturer of heavy-duty commercial vehicles known for their safety, durability, and advanced engineering.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Volvo Trucks Target entity description: Volvo Trucks is a leading global manufacturer of heavy-duty commercial vehicles known for their safety, durability, and advanced engineering.
-
A.
Volvo Group
chosen
Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
-
B.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
-
C.
Scania
Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
-
D.
Daimler Truck AG
Daimler Truck AG is a leading global commercial vehicle manufacturer specializing in trucks and buses, formed as an independent company after its separation from the former Daimler AG.
-
E.
PACCAR
PACCAR is a major American manufacturer of commercial trucks and related heavy-duty vehicles headquartered in Bellevue, Washington.
- F. None of above.
Provenance (5 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_69c6386784008190b0ac82804a4ee30e |
completed | March 27, 2026, 7:57 a.m. |
| NEDg | Description generation | batch_69c639eabaf88190bf81112cde6e8e99 |
completed | March 27, 2026, 8:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c63a8738ac8190af0bface4b18eea6 |
completed | March 27, 2026, 8:06 a.m. |
Created at: March 22, 2026, 4:31 p.m.