Triple

T14501491
Position Surface form Disambiguated ID Type / Status
Subject Gausdal E359649 entity
Predicate borders P224 FINISHED
Object Nord-Fron E433529 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: Nord-Fron | Statement: [Gausdal, borders, Nord-Fron]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nord-Fron
Context triple: [Gausdal, borders, Nord-Fron]
  • A. Nord-Fron chosen
    Nord-Fron is a rural municipality in Innlandet county, Norway, known for its mountainous landscapes, traditional farming communities, and location in the Gudbrandsdalen valley.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Nordre Land
    Nordre Land is a rural municipality in Innlandet county, Norway, known for its forests, lakes, and agricultural landscape in the traditional district of Land.
  • D. Romsdal
    Romsdal is a traditional district in Møre og Romsdal county in western Norway, known for its dramatic fjords, mountains, and the town of Molde.
  • E. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • 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_69d8279740308190af9df93a3af8592e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de94dfe484819086dd971606e6478e completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd7a420040819097ee73390d625338 completed May 8, 2026, 5:53 a.m.
Created at: April 10, 2026, 1:21 a.m.