Triple

T15276369
Position Surface form Disambiguated ID Type / Status
Subject Sogn og Fjordane E365150 entity
Predicate containsPart P35 FINISHED
Object Høyanger E1163278 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: Høyanger | Statement: [Sogn og Fjordane, containsPart, Høyanger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Høyanger
Context triple: [Sogn og Fjordane, containsPart, Høyanger]
  • A. Høyanger chosen
    Høyanger is a small industrial village and municipality in Vestland county, western Norway, known for its hydropower-based aluminum production and dramatic fjord landscape.
  • B. Orkanger
    Orkanger is a town in Trøndelag county, Norway, known as a regional commercial and service hub by the Orkdalsfjorden.
  • C. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • D. Hølen
    Hølen is a small historic village in Viken county, Norway, known for its past timber industry and picturesque setting along the Såna river.
  • E. Kragerø
    Kragerø is a coastal town in Norway renowned for its picturesque archipelago, historic wooden buildings, and role as a popular summer holiday destination.
  • 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_69d85a103d9081908c1ea6c4c73ac8e3 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e00953bc848190b83919f39d5ee37b completed April 15, 2026, 9:55 p.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ec2f35c8190a96af080cd7b6d0e completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 3:14 a.m.