Triple

T21298713
Position Surface form Disambiguated ID Type / Status
Subject Ørskog E524996 entity
Predicate borderedBy P224 FINISHED
Object Sykkylven 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: Sykkylven | Statement: [Ørskog, borderedBy, Sykkylven]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sykkylven
Context triple: [Ørskog, borderedBy, Sykkylven]
  • A. Sykkylven chosen
    Sykkylven is a municipality in Møre og Romsdal county, Norway, known for its fjord landscape and strong furniture manufacturing industry.
  • B. Sykkylvselva
    Sykkylvselva is a river in Sykkylven Municipality in Møre og Romsdal county, Norway, known for flowing through the Sykkylven valley into the Storfjorden.
  • C. Bykle
    Bykle is a small rural municipality in southern Norway known for its mountainous landscapes and outdoor recreation opportunities.
  • D. Synnervika
    Synnervika is a small lakeside locality in Norway that serves as a key access point and harbor area on the shores of Lake Femunden.
  • E. Skutvik
    Skutvik is a small coastal village in Hamarøy Municipality in Nordland county, Norway, known as a ferry port linking the mainland with the Lofoten Islands.
  • 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_69e0b517e6748190850d6f6ddf323d69 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7385a24d08190bfd410c7f10fa6f7 completed April 21, 2026, 8:42 a.m.
Created at: April 16, 2026, 4:05 p.m.