Triple

T19003447
Position Surface form Disambiguated ID Type / Status
Subject Brønderslev E465013 entity
Predicate locatedInGeographicalRegion P40 FINISHED
Object Vendsyssel 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: Vendsyssel | Statement: [Brønderslev, locatedInGeographicalRegion, Vendsyssel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vendsyssel
Context triple: [Brønderslev, locatedInGeographicalRegion, Vendsyssel]
  • A. Vendsyssel chosen
    Vendsyssel is a region in northern Denmark forming the northernmost part of the Jutland peninsula, known for its coastal landscapes and rural towns.
  • B. Norddjurs
    Norddjurs is a municipality in Denmark’s Central Jutland region, known for its coastal landscapes, rural communities, and small towns such as Grenaa.
  • C. Sogn
    Sogn is a traditional district in western Norway known for its dramatic fjord landscapes, including parts of the famous Sognefjord.
  • D. Frederikssund
    Frederikssund is a Danish town and municipality located on the island of Zealand, known for its Viking heritage and position along the Roskilde Fjord.
  • E. Abildsø
    Abildsø is a residential neighborhood in the borough of Østensjø in Oslo, Norway, known for its green areas and proximity to the lake Østensjøvannet.
  • 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_69d8dd01a56c81909694a128c66b21d7 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d6a252588190a40398b1879fb096 completed April 20, 2026, 7:32 a.m.
Created at: April 10, 2026, 12:01 p.m.