Triple

T6619431
Position Surface form Disambiguated ID Type / Status
Subject Larvik E149637 entity
Predicate administrativeCentre P1474 FINISHED
Object Larvik (town) E149637 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: Larvik (town) | Statement: [Larvik, administrativeCentre, Larvik (town)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Larvik (town)
Context triple: [Larvik, administrativeCentre, Larvik (town)]
  • A. Larvik chosen
    Larvik is a coastal town and municipality in Vestfold, Norway, known for its harbor, beaches, and historic connections to the shipping and timber industries.
  • B. Håvik
    Håvik is a small coastal village located in Karmøy municipality in Rogaland county, southwestern Norway.
  • C. Lørenskog
    Lørenskog is a suburban municipality in Viken county, Norway, located just east of Oslo and known for its residential areas and commercial centers.
  • D. Kjøpsvik
    Kjøpsvik is a small village in Nordland county, Norway, situated along the Tysfjorden and known as a local industrial and ferry hub in the region.
  • E. Stor-Elvdal
    Stor-Elvdal is a large, sparsely populated rural municipality in Innlandet county, Norway, known for its forests, river valleys, and outdoor recreation.
  • 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_69c687ed8a9c81908bb671717cb192ef completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6af5ca97481909f8a7dc47249b4d3 completed March 27, 2026, 4:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6e4461e748190b4feead6ef16a01c completed March 27, 2026, 8:10 p.m.
Created at: March 27, 2026, 1:58 p.m.