Triple
T6350401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volvo Group |
E142854
|
entity |
| Predicate | brand |
P1500
|
FINISHED |
| Object |
Volvo Buses
Volvo Buses is a global manufacturer of buses and bus chassis known for its focus on safety, reliability, and sustainable transport solutions.
|
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 Buses | Statement: [Volvo Group, brand, Volvo Buses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volvo Buses Context triple: [Volvo Group, brand, Volvo Buses]
-
A.
Daimler Buses
Daimler Buses is the bus and coach manufacturing division of Daimler AG, producing a wide range of commercial passenger vehicles for global markets.
-
B.
Solaris Bus & Coach
Solaris Bus & Coach is a Polish manufacturer of buses and trolleybuses widely used in public transport systems across Europe.
-
C.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
-
D.
Scania
Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
-
E.
Volvo Group
Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
- 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 Buses Triple: [Volvo Group, brand, Volvo Buses]
Generated description
Volvo Buses is a global manufacturer of buses and bus chassis known for its focus on safety, reliability, and sustainable transport solutions.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Volvo Buses Target entity description: Volvo Buses is a global manufacturer of buses and bus chassis known for its focus on safety, reliability, and sustainable transport solutions.
-
A.
Daimler Buses
Daimler Buses is the bus and coach manufacturing division of Daimler AG, producing a wide range of commercial passenger vehicles for global markets.
-
B.
Solaris Bus & Coach
Solaris Bus & Coach is a Polish manufacturer of buses and trolleybuses widely used in public transport systems across Europe.
-
C.
Scania
Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
-
D.
Scania
Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
-
E.
Volvo Group
chosen
Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
- 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_69c62d52cbd881908ac36eca108f3194 |
completed | March 27, 2026, 7:10 a.m. |
| NEDg | Description generation | batch_69c631ef5df8819094e0faf89cbe6971 |
completed | March 27, 2026, 7:29 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c6327c63308190be17cb1bf07259ce |
completed | March 27, 2026, 7:32 a.m. |
Created at: March 22, 2026, 4:31 p.m.