Triple

T18339398
Position Surface form Disambiguated ID Type / Status
Subject Tysfjorden E439360 entity
Predicate hasSettlementOnShore P16159 FINISHED
Object Kjøpsvik 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: Kjøpsvik | Statement: [Tysfjorden, hasSettlementOnShore, Kjøpsvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kjøpsvik
Context triple: [Tysfjorden, hasSettlementOnShore, Kjøpsvik]
  • A. Kjøpsvik chosen
    Kjøpsvik is a small village in Nordland county, Norway, situated along the Tysfjorden and known as a local industrial and ferry hub in the region.
  • B. Vedvik
    Vedvik is a small coastal village in the former Vågsøy municipality in Vestland county, western Norway.
  • C. Røyrvik
    Røyrvik is a small rural municipality in Trøndelag county, Norway, known for its mountainous landscapes, reindeer herding traditions, and proximity to Børgefjell National Park.
  • D. Kleppstad
    Kleppstad is a small coastal village in northern Norway, situated on the island of Austvågøy in the Lofoten archipelago.
  • E. Eidsvik
    Eidsvik is a small village located in the former municipality of Haram in Møre og Romsdal county, Norway.
  • 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_69d8b9175fec8190af865699b4e64d8c completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50ed07db48190a15e957c96b1c5bf completed April 19, 2026, 5:20 p.m.
Created at: April 10, 2026, 10:37 a.m.