Triple

T4201765
Position Surface form Disambiguated ID Type / Status
Subject Hovdetoppen E86082 entity
Predicate partOf P40 FINISHED
Object Gjøvik urban area E84018 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: Gjøvik urban area | Statement: [Hovdetoppen, partOf, Gjøvik urban area]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gjøvik urban area
Context triple: [Hovdetoppen, partOf, Gjøvik urban area]
  • A. Fredrikstad/Sarpsborg urban area
    The Fredrikstad/Sarpsborg urban area is a major contiguous metropolitan region in southeastern Norway that encompasses the twin cities of Fredrikstad and Sarpsborg.
  • B. Gjøvik chosen
    Gjøvik is a town and municipality in Innlandet county, Norway, known for its location along Lake Mjøsa and its mix of industrial heritage and modern sports and cultural facilities.
  • C. Greater Oslo Region
    The Greater Oslo Region is the metropolitan area surrounding Norway’s capital, encompassing Oslo and its neighboring municipalities as a unified economic and commuter region.
  • D. Gjøvik Region
    Gjøvik Region is a regional area in Innlandet county, Norway, centered around the town of Gjøvik and its surrounding municipalities.
  • E. Sagene district
    Sagene district is a central borough of Oslo, Norway, known for its historic industrial areas, riverside parks, and vibrant urban neighborhoods.
  • 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_69aed93b89f48190a31f6d57c760e42f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af037da30481908106b27a88d59140 completed March 9, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5a84d00b8819082982c4d229c450e completed March 14, 2026, 6:26 p.m.
Created at: March 9, 2026, 3:49 p.m.