Triple

T6762293
Position Surface form Disambiguated ID Type / Status
Subject Vegårshei E154623 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Åmli E150931 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: Åmli | Statement: [Vegårshei, neighboringMunicipality, Åmli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Åmli
Context triple: [Vegårshei, neighboringMunicipality, Åmli]
  • A. Åmli chosen
    Åmli is a rural municipality in Agder county in southern Norway, known for its forested landscapes, rivers, and outdoor recreation opportunities.
  • B. Årnes
    Årnes is a small Norwegian town situated along the Glomma River, known as a local administrative and commercial center in Nes municipality in Viken county.
  • C. Bjerke
    Bjerke is a neighborhood in the Bjerke borough of Oslo, Norway, known primarily as a residential area with local services and amenities.
  • D. Sæbø
    Sæbø is a small Norwegian village known for its scenic location amid steep mountains and fjord landscapes in western Norway.
  • E. Mosvik
    Mosvik was a former municipality in Trøndelag county, Norway, known for its rural landscape and coastal location along the Trondheimsfjord.
  • 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_69c688109c1c8190added9a221292af0 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d21444dc8190a290af86c81e96a5 completed March 27, 2026, 6:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c712b6ec408190bd9131f289b02ba7 completed March 27, 2026, 11:28 p.m.
Created at: March 27, 2026, 2:12 p.m.