Triple

T15575102
Position Surface form Disambiguated ID Type / Status
Subject Aurland E374347 entity
Predicate contains P35 FINISHED
Object Gudvangen E393104 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: Gudvangen | Statement: [Aurland, contains, Gudvangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gudvangen
Context triple: [Aurland, contains, Gudvangen]
  • A. Gudvangen chosen
    Gudvangen is a small village in western Norway known for its dramatic fjord landscape and role as a popular tourist gateway to the Nærøyfjord.
  • B. Kalvåg
    Kalvåg is a coastal fishing village in Bremanger Municipality in Vestland county, Norway, known for its well-preserved wooden waterfront buildings and maritime heritage.
  • C. Gjesvær
    Gjesvær is a small coastal fishing village in northern Norway known for its rich birdlife and proximity to the North Cape.
  • D. Gressvik
    Gressvik is a village in Fredrikstad Municipality in Viken county, Norway, located on the western side of the Glomma River.
  • E. Honningsvåg
    Honningsvåg is a small Arctic port town in northern Norway, often used as a gateway to the North Cape and a popular stop for cruise and coastal voyages.
  • 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_69d85ccd575081908909b71a3f3e3a61 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e2140388190a8df7b835eaa72ce completed April 16, 2026, 2:49 a.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbf2567c81909ab6054ade27afac completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 4:10 a.m.