Triple

T10429637
Position Surface form Disambiguated ID Type / Status
Subject Tunevannet E245874 entity
Predicate region P40 FINISHED
Object Østfold region E96296 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: Østfold region | Statement: [Tunevannet, region, Østfold region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Østfold region
Context triple: [Tunevannet, region, Østfold region]
  • A. Østfold chosen
    Østfold is a former county in southeastern Norway known for its coastal landscape along the Oslofjord, historic fortresses, and proximity to the Swedish border.
  • B. North Denmark Region
    North Denmark Region is an administrative region in northern Denmark that encompasses the northernmost part of the Jutland Peninsula, including Aalborg as its largest city.
  • C. Østlandet
    Østlandet is the most populous region of southeastern Norway, encompassing the capital city Oslo and surrounding inland and coastal areas.
  • D. Agder
    Agder is a county in southern Norway known for its long coastline, maritime heritage, and popular coastal towns and islands.
  • E. Århus County
    Århus County was a former administrative county in eastern Jutland, Denmark, centered on the city of Aarhus, that existed until the 2007 municipal reform.
  • 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_69d381bf3dc08190bf35a2643e4e8f22 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4ea4b4b5881908ae23f8efeea482b completed April 7, 2026, 11:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3a8e98cac8190873af1a2cdb5c5a9 completed April 18, 2026, 3:53 p.m.
Created at: April 6, 2026, 12:13 p.m.