Triple

T13398287
Position Surface form Disambiguated ID Type / Status
Subject Gryllefjord E319757 entity
Predicate locatedIn P40 FINISHED
Object Troms og Finnmark E81316 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: Troms og Finnmark | Statement: [Gryllefjord, locatedIn, Troms og Finnmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troms og Finnmark
Context triple: [Gryllefjord, locatedIn, Troms og Finnmark]
  • A. Troms og Finnmark chosen
    Troms og Finnmark is Norway’s northernmost and largest county, known for its Arctic landscapes, Sami culture, and phenomena like the midnight sun and northern lights.
  • B. Finnmark
    Finnmark is a sparsely populated, historically Norwegian region in the far northeast of Scandinavia, known for its Arctic climate, Sami culture, and dramatic coastal and tundra landscapes.
  • C. Hålogaland
    Hålogaland is a historical region in northern Norway traditionally encompassing parts of what are now Troms and Nordland counties.
  • D. Nordland county
    Nordland county is a long, coastal region in northern Norway known for its dramatic fjords, islands, and Arctic landscapes.
  • E. Møre og Romsdal
    Møre og Romsdal is a coastal county in western Norway known for its dramatic fjords, islands, and mountainous 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_69d806b943cc8190b6af624d385d7e12 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dba0d9e7348190844e11dd6cbd13b0 completed April 12, 2026, 1:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7a83382e88190bfb229f9bab59b17 completed May 3, 2026, 7:55 p.m.
Created at: April 9, 2026, 9:34 p.m.