Triple

T13521536
Position Surface form Disambiguated ID Type / Status
Subject Kvæfjord E322907 entity
Predicate hasNeighbour P5707 FINISHED
Object Lødingen E316361 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: Lødingen | Statement: [Kvæfjord, hasNeighbour, Lødingen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lødingen
Context triple: [Kvæfjord, hasNeighbour, Lødingen]
  • A. Lødingen chosen
    Lødingen is a coastal municipality in Nordland county, Norway, located on the island of Hinnøya and known for its fishing, maritime activities, and scenic fjord landscape.
  • B. Lodalen
    Lodalen is a small valley and residential-industrial area in Oslo, Norway, situated near the inner-city districts and railway facilities.
  • C. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • D. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • E. Nadderud
    Nadderud is a residential and sports-focused area in Bærum, Norway, known for its stadium and athletic facilities.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbafa3df0c8190804174695587f0ea completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7549a215c8190a0b18c505d8ca504 completed May 3, 2026, 1:58 p.m.
Created at: April 9, 2026, 9:44 p.m.