Triple

T20018465
Position Surface form Disambiguated ID Type / Status
Subject Ulstein E494783 entity
Predicate neighboringMunicipality P17964 FINISHED
Object Volda NE NERFINISHED

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: Volda | Statement: [Ulstein, neighboringMunicipality, Volda]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Volda
Context triple: [Ulstein, neighboringMunicipality, Volda]
  • A. Volda chosen
    Volda is a municipality in Møre og Romsdal county, Norway, known for its fjord landscape, cultural life, and Volda University College.
  • B. 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.
  • C. Randesund
    Randesund is a coastal district of Kristiansand in southern Norway, known for its scenic archipelago, beaches, and recreational outdoor areas.
  • D. Suldal
    Suldal is a large rural municipality in southwestern Norway known for its fjords, mountains, and hydroelectric power production.
  • E. Mjøsund
    Mjøsund is a small coastal settlement in northern Norway, situated on or near the island of Andørja and known for its scenic fjord landscape and maritime setting.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6623e40748190b1abb0ead9acab4e completed April 20, 2026, 5:28 p.m.
Created at: April 11, 2026, 3:34 p.m.