Triple

T15345205
Position Surface form Disambiguated ID Type / Status
Subject Ulvik E366898 entity
Predicate locatedIn P40 FINISHED
Object Hardanger region E1144700 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: Hardanger region | Statement: [Ulvik, locatedIn, Hardanger region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hardanger region
Context triple: [Ulvik, locatedIn, Hardanger region]
  • A. Hardangerfjorden region chosen
    The Hardangerfjorden region is a scenic area in western Norway centered around the Hardangerfjord, renowned for its dramatic fjord landscapes, fruit orchards, and traditional coastal communities.
  • B. Dovre region
    The Dovre region is a mountainous area in central Norway known for its rugged landscapes, national parks, and rich wildlife, including wild reindeer.
  • C. Sunnfjord region
    The Sunnfjord region is a coastal district in western Norway known for its deep fjords, rugged mountains, and traditional rural communities.
  • D. Nord-Valdres
    Nord-Valdres is the northern part of the traditional Valdres district in Innlandet county, Norway, known for its mountainous landscapes, valleys, and rural communities.
  • E. Fjordane
    Fjordane is a traditional district in western Norway known for its dramatic fjord landscapes and coastal scenery.
  • 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e163a3c8190ab933411372c1573 completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0319f248190a37c9afa09c32428 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 3:17 a.m.