Triple

T3579238
Position Surface form Disambiguated ID Type / Status
Subject Lysefjord E75760 entity
Predicate hasCliff P11724 FINISHED
Object Preikestolen E365816 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: Preikestolen | Statement: [Lysefjord, hasCliff, Preikestolen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Preikestolen
Context triple: [Lysefjord, hasCliff, Preikestolen]
  • A. Preikestolen chosen
    Preikestolen is a famous steep cliff and viewpoint in southwestern Norway that towers over the Lysefjord and attracts many hikers and tourists.
  • B. Galdhøpiggen
    Galdhøpiggen is the highest mountain in Norway and Scandinavia, located in the Jotunheimen range.
  • C. Higravstinden
    Higravstinden is a prominent mountain peak in Norway’s Lofoten archipelago, known for its rugged alpine terrain and striking coastal views.
  • D. Haraldshaugen national monument
    Haraldshaugen national monument is a historic memorial in Haugesund, Norway, traditionally regarded as marking the burial site of Norway’s first king, Harald Fairhair.
  • E. St. Hanshaugen
    St. Hanshaugen is a central borough of Oslo, Norway, known for its large hillside park and vibrant urban residential areas.
  • 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_69ad85d5e3008190bdfe0bacdd1f5a1b completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc0defe14819095a337a840e33300 completed March 8, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69b3bbc6bc948190a517639f5d79c0a3 completed March 13, 2026, 7:24 a.m.
Created at: March 8, 2026, 3:21 p.m.