Triple

T18150654
Position Surface form Disambiguated ID Type / Status
Subject Sørkjosen E434491 entity
Predicate locatedInMunicipality P40 FINISHED
Object Nordreisa NE NERFINISHED

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: Nordreisa | Statement: [Sørkjosen, locatedInMunicipality, Nordreisa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordreisa
Context triple: [Sørkjosen, locatedInMunicipality, Nordreisa]
  • A. Nordreisa chosen
    Nordreisa is a municipality in Troms og Finnmark county in northern Norway, known for its deep Reisa Valley, Reisa National Park, and dramatic waterfalls and river landscapes.
  • B. Finnsnes
    Finnsnes is a small coastal town in northern Norway that serves as a commercial and transport hub for the island municipality of Senja.
  • C. Skogvika
    Skogvika is a small coastal settlement on the island of Rebbenesøya in northern Norway.
  • D. Asmaløy
    Asmaløy is one of the main inhabited islands in the Hvaler archipelago in southeastern Norway, known for its coastal scenery and holiday homes.
  • E. Hjørungavåg
    Hjørungavåg is a small coastal village in western Norway, known for its scenic fjord landscape and maritime heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b90aac308190801e2c57d8c5bfe5 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4de3812e8819097f025476d5c6a1d completed April 19, 2026, 1:52 p.m.
Created at: April 10, 2026, 10:29 a.m.