Triple

T17370396
Position Surface form Disambiguated ID Type / Status
Subject Lifjell E422293 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Bø i Telemark NE ONNED1

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: Bø i Telemark | Statement: [Lifjell, hasNearbySettlement, Bø i Telemark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bø i Telemark
Context triple: [Lifjell, hasNearbySettlement, Bø i Telemark]
  • A.
    Bø is a coastal municipality in Nordland county, Norway, known for its dramatic landscapes, fishing heritage, and location within the Vesterålen archipelago.
  • B. chosen
    Bø is a small town in southern Norway known for its scenic landscapes, outdoor recreation, and role as a local commercial and educational center.
  • C. Bøelva
    Bøelva is a river in Telemark, Norway, known for flowing through the Bø area before emptying into the large lake Norsjø.
  • D. Bøstad
    Bøstad is a small village in the Lofoten archipelago of Nordland county, Norway, known for its scenic coastal landscape and proximity to Viking-era historical sites.
  • E. Bøvra
    Bøvra is a river in Lom Municipality in Innlandet county, Norway, known for flowing through a mountainous valley landscape.
  • 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_69d889d6535c81908be333c01deaec4e completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a68ff448190b505861e56df5b6d completed April 19, 2026, 2:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a019568a27c8190af1bbe6db75f3e6f in_progress May 11, 2026, 8:38 a.m.
Created at: April 10, 2026, 5:44 a.m.