Triple

T15690309
Position Surface form Disambiguated ID Type / Status
Subject Voss Municipality E380310 entity
Predicate administrativeCentre P1474 FINISHED
Object Vossevangen E739588 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: Vossevangen | Statement: [Voss Municipality, administrativeCentre, Vossevangen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vossevangen
Context triple: [Voss Municipality, administrativeCentre, Vossevangen]
  • A. Vossevangen chosen
    Vossevangen is a village in western Norway that serves as the main commercial and cultural hub of the Voss region, known for its scenic surroundings and outdoor activities.
  • B. Freifjord
    Freifjord is a fjord in western Norway known for its scenic coastal landscape and proximity to historic sites such as Kvernes Church.
  • C. Vestfossen
    Vestfossen is a village in Buskerud, Norway, known for its industrial heritage and contemporary art scene, including the Vestfossen Kunstlaboratorium.
  • D. Longva
    Longva is a small village in Norway’s Møre og Romsdal county, situated within the municipality of Haram on the island-dotted western coast.
  • E. Vangsmjøse
    Vangsmjøse is a lake in the Valdres region of Innlandet county, Norway, known for its scenic mountain surroundings and clear waters.
  • 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_69d86d99e860819094b6957cde470f2c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e04f4e59988190aaf12f6a07c8f0e4 completed April 16, 2026, 2:54 a.m.
NED1 Entity disambiguation (via context triple) batch_6a000ec1091c8190a8e4c4db6180129a completed May 10, 2026, 4:51 a.m.
Created at: April 10, 2026, 4:44 a.m.