Triple

T15216736
Position Surface form Disambiguated ID Type / Status
Subject Sogn region E363655 entity
Predicate containsSettlement P847 FINISHED
Object Kaupanger E363658 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: Kaupanger | Statement: [Sogn region, containsSettlement, Kaupanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaupanger
Context triple: [Sogn region, containsSettlement, Kaupanger]
  • A. Kaupanger chosen
    Kaupanger is a village in Vestland county, Norway, known for its historic stave church and its location along the inner Sognefjord.
  • B. Kristinestad
    Kristinestad is a small coastal town in western Finland known for its well-preserved wooden old town and historic maritime character.
  • C. Tonstad
    Tonstad is a small village in Agder county, Norway, serving as the administrative and commercial center of Sirdal municipality.
  • D. Smestad
    Smestad is a residential neighborhood in Oslo, Norway, known for its affluent housing and proximity to green areas and good public transport.
  • E. Kaup
    Kaup refers to Johann Jakob Kaup, a 19th-century German naturalist and zoologist known for his taxonomic work in classifying fishes and other vertebrates.
  • 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_69d85a0ce24c81909c4d3b6475548c95 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e0076f90c481909989befe031a2cae completed April 15, 2026, 9:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69fed343f51481908f04c35d37b39ad2 completed May 9, 2026, 6:25 a.m.
Created at: April 10, 2026, 3:11 a.m.