Triple

T15694285
Position Surface form Disambiguated ID Type / Status
Subject Kuglhorn E380415 entity
Predicate locatedIn P40 FINISHED
Object Nordland county, Norway E401032 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: Nordland county, Norway | Statement: [Kuglhorn, locatedIn, Nordland county, Norway]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordland county, Norway
Context triple: [Kuglhorn, locatedIn, Nordland county, Norway]
  • A. Nordland county chosen
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • B. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • C. Helgeland
    Helgeland is a coastal region in northern Norway known for its dramatic fjords, islands, and mountain landscapes.
  • D. Voss, Norway
    Voss, Norway is a scenic town in western Norway known for its dramatic fjord and mountain landscapes and as a hub for outdoor sports and adventure tourism.
  • E. 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.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f50ce848190a839c4fb7306d793 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6eed9a8c8190a57ffce61a27ec17 completed May 9, 2026, 5:29 p.m.
Created at: April 10, 2026, 4:44 a.m.