Triple

T14586268
Position Surface form Disambiguated ID Type / Status
Subject Køge Bay E342322 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Brøndby E548723 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: Brøndby | Statement: [Køge Bay, hasNearbySettlement, Brøndby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brøndby
Context triple: [Køge Bay, hasNearbySettlement, Brøndby]
  • A. Brøndby chosen
    Brøndby is a suburban municipality in the western part of the Copenhagen metropolitan area in Denmark, known for its residential districts and the football club Brøndby IF.
  • B. Lyngby BK
    Lyngby BK is a Danish professional football club based in Kongens Lyngby that competes in the country’s top leagues and has developed and hosted numerous international players.
  • C. Hammersborg
    Hammersborg is a central neighborhood in Oslo, Norway, known for housing key government buildings and cultural institutions.
  • D. Odense Boldklub
    Odense Boldklub is a Danish professional football club based in the city of Odense, known for competing in the top tiers of Danish football.
  • E. Randers FC
    Randers FC is a professional Danish football club based in the city of Randers that competes in the Danish Superliga.
  • 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_69d822ddc0f081909cd8163c7de298cd completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb421bb308190a457425429ef6aa5 completed April 14, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd94bef27481908c108110dbf21780 completed May 8, 2026, 7:46 a.m.
Created at: April 10, 2026, 1:24 a.m.