Triple

T597118
Position Surface form Disambiguated ID Type / Status
Subject Sámi E11410 entity
Predicate region P40 FINISHED
Object Sápmi E73789 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: Sápmi | Statement: [Sámi, region, Sápmi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sápmi
Context triple: [Sámi, region, Sápmi]
  • A. Lapland chosen
    Lapland is a sparsely populated Arctic region in northern Finland known for its subarctic wilderness, indigenous Sámi culture, and reputation as the home of Santa Claus.
  • B. Vestland
    Vestland is a county in western Norway known for its dramatic fjords, coastal landscapes, and the city of Bergen.
  • C. Nord
    Nord is a department in northern France known for its industrial heritage, dense population, and proximity to Belgium.
  • D. Scandinavia
    Scandinavia is a cultural and geographical region in Northern Europe, typically comprising Norway, Sweden, and Denmark, known for its high living standards, social welfare systems, and distinctive Nordic culture.
  • 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_69a4932779b881908688590d59c71900 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49d2b98d08190a1c1e8659efdfd75 completed March 1, 2026, 8:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69a580335a5c819096d0c105178c4ad7 completed March 2, 2026, 12:18 p.m.
Created at: March 1, 2026, 7:35 p.m.