Triple

T15760489
Position Surface form Disambiguated ID Type / Status
Subject Lebesby E382081 entity
Predicate borderedBy P224 FINISHED
Object Tana municipality E1022318 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: Tana municipality | Statement: [Lebesby, borderedBy, Tana municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tana municipality
Context triple: [Lebesby, borderedBy, Tana municipality]
  • A. Tana municipality chosen
    Tana municipality is a sparsely populated local government area in Troms og Finnmark county in northern Norway, known for the Tana River, rich Sami culture, and Arctic wilderness.
  • B. Gagnef Municipality
    Gagnef Municipality is a local government area in Dalarna County, central Sweden, known for its rural landscapes, traditional culture, and location at the confluence of major rivers.
  • C. Anton Municipality
    Anton Municipality is a small administrative municipality located within Sofia Province in western Bulgaria.
  • D. Soteapan municipality
    Soteapan municipality is a region in the Mexican state of Veracruz known for its indigenous communities and use of the Sierra Popoluca language.
  • E. Avannaata municipality
    Avannaata municipality is a large local government area in northwestern Greenland that includes remote Arctic regions such as the Thule area and several coastal settlements.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e050b52c548190a0ffa4493a4eb15c completed April 16, 2026, 3 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8774eda08190a6231b4fd5027e6f completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:47 a.m.