Triple

T1903661
Position Surface form Disambiguated ID Type / Status
Subject Scania E37748 entity
Predicate hasSubsidiary P254 FINISHED
Object Scania (Great Britain) Limited E37748 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: Scania (Great Britain) Limited | Statement: [Scania, hasSubsidiary, Scania (Great Britain) Limited]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scania (Great Britain) Limited
Context triple: [Scania, hasSubsidiary, Scania (Great Britain) Limited]
  • A. Scania chosen
    Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
  • B. Scania
    Scania is a historical province in southern Sweden known for its fertile farmland, coastal landscapes, and former status as part of Denmark.
  • C. Volvo Group
    Volvo Group is a Swedish multinational manufacturing company best known for producing trucks, buses, construction equipment, and marine and industrial engines.
  • D. Neoplan
    Neoplan is a German bus and coach manufacturer renowned for its innovative, high-end touring and city buses.
  • E. Volvo Cars
    Volvo Cars is a Swedish automotive manufacturer known for its focus on safety, practical design, and premium vehicles.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb1909aec8190b3259c8f969ce81e completed March 7, 2026, 5:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfba998e88190a4692d3aefa09806 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:35 p.m.