Triple

T13471594
Position Surface form Disambiguated ID Type / Status
Subject Averøy Municipality E311640 entity
Predicate hasSettlement P1068 FINISHED
Object Bremsnes E316580 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: Bremsnes | Statement: [Averøy Municipality, hasSettlement, Bremsnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bremsnes
Context triple: [Averøy Municipality, hasSettlement, Bremsnes]
  • A. Bremsnes chosen
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • B. Fosnes
    Fosnes was a former rural municipality in Trøndelag county, Norway, known for its coastal landscape and small, dispersed population.
  • 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. Ottosdal
    Ottosdal is a small agricultural town in South Africa’s North West province, known for its grain farming and rural character.
  • E. Bjugn
    Bjugn is a former municipality and coastal community in Trøndelag county, Norway, known for its fishing, agriculture, and location on the Fosen peninsula.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaf22e5f88190b1078f006c8ef7c0 completed April 12, 2026, 2:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b8c49e9c819088e6e98aa53d05fa completed May 3, 2026, 9:06 p.m.
Created at: April 9, 2026, 9:42 p.m.