Triple

T13953912
Position Surface form Disambiguated ID Type / Status
Subject Jevnaker municipality E335604 entity
Predicate partOfRegion P285 FINISHED
Object Hadeland E337526 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: Hadeland | Statement: [Jevnaker municipality, partOfRegion, Hadeland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hadeland
Context triple: [Jevnaker municipality, partOfRegion, Hadeland]
  • A. Hadeland chosen
    Hadeland is a traditional rural district in southeastern Norway known for its agricultural landscape, historic churches, and the Hadeland Glassverk glassworks.
  • B. Haugalandet
    Haugalandet is a coastal region in western Norway centered around the town of Haugesund, known for its maritime heritage and North Sea industries.
  • C. Hjelmeland
    Hjelmeland is a rural municipality in southwestern Norway known for its fjord landscapes, agriculture, and traditional fruit farming.
  • D. Suldal
    Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
  • E. Helleland
    Helleland is a small village in Rogaland county, Norway, situated within the municipality of Eigersund.
  • 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_69d81c6081b88190b53e317c3370c8fe completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2e146720819085d0f5eae558b7a4 completed April 14, 2026, 12:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdf06cddcc81909a1ba268f667dc1d completed May 8, 2026, 2:17 p.m.
Created at: April 9, 2026, 10:17 p.m.