Triple

T15750983
Position Surface form Disambiguated ID Type / Status
Subject Porsáŋgguvuotna E381842 entity
Predicate hasMunicipality P847 FINISHED
Object Lebesby E382081 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: Lebesby | Statement: [Porsáŋgguvuotna, hasMunicipality, Lebesby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lebesby
Context triple: [Porsáŋgguvuotna, hasMunicipality, Lebesby]
  • A. Lebesby chosen
    Lebesby is a sparsely populated coastal municipality in Troms og Finnmark county in northern Norway, known for its Arctic landscapes, fishing communities, and proximity to the Barents Sea.
  • B. Edsbyn
    Edsbyn is a small town in Gävleborg County, Sweden, known for its bandy team and role as a local industrial and service center.
  • C. Treseburg
    Treseburg is a small village in the Harz Mountains of central Germany, known as a scenic gateway for hiking and nature tourism in the surrounding Bode Valley.
  • D. Nesseby
    Nesseby is a small coastal municipality in Troms og Finnmark county in northern Norway, known for its Sámi culture and location along the Varangerfjorden.
  • E. Mörby
    Mörby is a locality in the Stockholm area of Sweden served by a station on the Roslagsbanan narrow-gauge railway line.
  • 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_69e05030e31081908c307a8dc7067db4 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff876d48588190afec7722cca25633 completed May 9, 2026, 7:13 p.m.
Created at: April 10, 2026, 4:47 a.m.