Triple

T20220587
Position Surface form Disambiguated ID Type / Status
Subject Vanylven E495241 entity
Predicate hasSettlement P1068 FINISHED
Object Slagnes 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: Slagnes | Statement: [Vanylven, hasSettlement, Slagnes]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Slagnes
Context triple: [Vanylven, hasSettlement, Slagnes]
  • A. Slagnes chosen
    Slagnes is a small settlement located within Vanylven Municipality in Møre og Romsdal county, Norway.
  • B. Bremsnes
    Bremsnes is a village on the island of Averøya in Møre og Romsdal county, Norway, known for its coastal setting and local church.
  • C. Flesberg
    Flesberg is a rural municipality in southeastern Norway known for its forests, traditional wooden architecture, and location in the Numedal valley.
  • D. 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.
  • E. Solør
    Solør is a traditional district in Eastern Norway known for its rural landscapes, forestry, and agriculture.
  • 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_69da626cff80819097b530718a7c98b6 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66edc88148190b003b72eb4c69da5 completed April 20, 2026, 6:22 p.m.
Created at: April 11, 2026, 11:39 p.m.