Triple

T13808301
Position Surface form Disambiguated ID Type / Status
Subject Vestre Toten municipality E331815 entity
Predicate hasSettlement P1068 FINISHED
Object Raufoss E470951 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: Raufoss | Statement: [Vestre Toten municipality, hasSettlement, Raufoss]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Raufoss
Context triple: [Vestre Toten municipality, hasSettlement, Raufoss]
  • A. Raufoss chosen
    Raufoss is an industrial town in Norway known for its manufacturing sector, particularly in defense and automotive components.
  • B. Bardufoss
    Bardufoss is a town in northern Norway known for its military base, including the main headquarters of the Norwegian Army in the region, and its nearby airport.
  • C. Sogndal
    Sogndal is a village and municipality in Vestland county, Norway, known for its scenic fjord landscape, agriculture, and as a regional education and service center.
  • D. Risør
    Risør is a small coastal town in southern Norway known for its well-preserved wooden houses, maritime heritage, and annual wooden boat festival.
  • E. Farsund
    Farsund is a coastal town and municipality in southern Norway known for its maritime heritage, beaches, and historic wooden architecture.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026eae8481908b8880635e6a9152 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe0cce10c88190bf25404fc4c75bbf completed May 8, 2026, 4:18 p.m.
Created at: April 9, 2026, 10:12 p.m.