Triple

T17505102
Position Surface form Disambiguated ID Type / Status
Subject Dyrøya E426292 entity
Predicate hasVillage P4011 FINISHED
Object Brøstadbotn 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: Brøstadbotn | Statement: [Dyrøya, hasVillage, Brøstadbotn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brøstadbotn
Context triple: [Dyrøya, hasVillage, Brøstadbotn]
  • A. Brøstadbotn chosen
    Brøstadbotn is a small coastal village in Northern Norway that serves as the administrative centre of Dyrøy Municipality in Troms county.
  • B. Kjeldebotn
    Kjeldebotn is a small village in northern Norway that forms part of the municipality of Ballangen in Nordland county.
  • C. Jørstadmoen
    Jørstadmoen is a military base and village area in Lillehammer, Norway, known primarily as a key site for the Norwegian Armed Forces and home to important defense and cyber units.
  • D. Vålebru
    Vålebru is a village in Innlandet county, Norway, serving as the main local hub for services and administration in Ringebu municipality.
  • E. Stryn
    Stryn is a municipality in Vestland county, Norway, known for its dramatic fjord and mountain landscapes, glaciers, and popular outdoor tourism activities.
  • 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_69d889dd9164819087b1dc3c9240c870 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e45214d44c8190b1bf04bf24ab8e81 completed April 19, 2026, 3:55 a.m.
Created at: April 10, 2026, 5:48 a.m.