Triple

T16424994
Position Surface form Disambiguated ID Type / Status
Subject Duke of Skåne E398919 entity
Predicate associatedWithRegion P285 FINISHED
Object Scania E138516 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 | Statement: [Duke of Skåne, associatedWithRegion, Scania]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Scania
Context triple: [Duke of Skåne, associatedWithRegion, Scania]
  • A. Scania
    Scania is a Swedish manufacturer renowned for its heavy trucks, buses, and industrial and marine engines.
  • B. Scania chosen
    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_69d87f2b9024819085c20e52de95d583 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328f9da9081908dadbdac4b2d38ec completed April 18, 2026, 6:47 a.m.
NED1 Entity disambiguation (via context triple) batch_6a003c5bcc7c81909dc1d3a9a1b7f50a completed May 10, 2026, 8:05 a.m.
Created at: April 10, 2026, 5:09 a.m.