Triple

T9883439
Position Surface form Disambiguated ID Type / Status
Subject Ofoten district E180868 entity
Predicate hasMainUrbanCentre P2106 FINISHED
Object Narvik E33599 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: Narvik | Statement: [Ofoten district, hasMainUrbanCentre, Narvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narvik
Context triple: [Ofoten district, hasMainUrbanCentre, Narvik]
  • A. Narvik chosen
    Narvik is a port town in northern Norway known for its strategic importance during World War II and as the site of major naval and land battles.
  • B. Kiruna
    Kiruna is a mining town in northern Sweden known for its large iron ore mine and its location above the Arctic Circle.
  • C. Karasjok
    Karasjok is a municipality in northern Norway known as a cultural and political center for the Sámi people.
  • D. Notodden
    Notodden is a town and municipality in Vestfold og Telemark county, Norway, known for its industrial heritage and annual blues festival.
  • E. Piteå
    Piteå is a coastal town in northern Sweden known for its historic wooden architecture, archipelago, and role as a regional cultural and industrial center in Norrbotten County.
  • 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_69ca828082cc8190a40f8d299caa6545 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cdb453b388819095a5070399d9788d completed April 2, 2026, 12:12 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1eaf0afcc81908d263df7651958e2 completed April 5, 2026, 4:54 a.m.
Created at: March 30, 2026, 8:38 p.m.