Triple

T13262596
Position Surface form Disambiguated ID Type / Status
Subject Finnsnes E315835 entity
Predicate region P40 FINISHED
Object Nord-Norge E17350 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-Norge | Statement: [Finnsnes, region, Nord-Norge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nord-Norge
Context triple: [Finnsnes, region, Nord-Norge]
  • A. Nordlandet
    Nordlandet is one of the main islands and districts of the coastal Norwegian city of Kristiansund.
  • B. Northern Norway chosen
    Northern Norway is the sparsely populated, Arctic-influenced northern region of Norway known for its dramatic coastal landscapes, midnight sun, and frequent displays of the Northern Lights.
  • C. Nordland
    Nordland is a long coastal county in northern Norway known for its dramatic fjords, islands like the Lofoten archipelago, and Arctic landscapes.
  • D. Vestlandet
    Vestlandet is the western region of Norway, known for its dramatic fjords, mountains, and coastal landscapes.
  • 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_69d806b1d9ac8190852c5571d5bd5f0f completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d9901b380881909e6520fbb6811084 completed April 11, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69f77f7846008190aa27fafe19056807 completed May 3, 2026, 5:01 p.m.
Created at: April 9, 2026, 9:25 p.m.