Triple

T15302845
Position Surface form Disambiguated ID Type / Status
Subject Hardanger E365829 entity
Predicate hasPart P35 FINISHED
Object Ulvik E366898 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: Ulvik | Statement: [Hardanger, hasPart, Ulvik]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ulvik
Context triple: [Hardanger, hasPart, Ulvik]
  • A. Ulvik chosen
    Ulvik is a small scenic municipality and village area in Vestland county, Norway, known for its fjord landscape, fruit orchards, and location along the inner reaches of the Hardanger region.
  • B. Ulsrud
    Ulsrud is a residential neighborhood in the Østensjø borough of Oslo, Norway, known for its proximity to Ulsrudvannet lake and access to public transportation.
  • C. Iveland
    Iveland is a small rural municipality in southern Norway known for its forests, agriculture, and mineral resources.
  • D. Sennesvik
    Sennesvik is a small coastal village located on the island of Vestvågøy in Norway’s Lofoten archipelago.
  • E. Ulvila
    Ulvila is a historic town and municipality in western Finland, located in the Satakunta region along the Kokemäki River.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ccd575c8190aa43262d3b73ef3c completed April 16, 2026, 1:35 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01e47d8c8190844d45dda9a3e5ea completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:15 a.m.