Triple

T19536874
Position Surface form Disambiguated ID Type / Status
Subject Niels Brock Copenhagen Business College E488788 entity
Predicate hasCampusIn P4623 FINISHED
Object Nørrebro 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: Nørrebro | Statement: [Niels Brock Copenhagen Business College, hasCampusIn, Nørrebro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nørrebro
Context triple: [Niels Brock Copenhagen Business College, hasCampusIn, Nørrebro]
  • A. Nørrebro chosen
    Nørrebro is a vibrant, multicultural district in Copenhagen known for its lively street life, diverse communities, and mix of historic and modern urban culture.
  • B. Vesterbro
    Vesterbro is a vibrant, formerly working-class district of Copenhagen known for its trendy bars, restaurants, and cultural scene.
  • C. Østerbro district
    Østerbro district is a central, affluent neighborhood in Copenhagen, Denmark, known for its waterfront areas, green spaces, and elegant residential streets.
  • D. Indre By
    Indre By is the historic city center of Copenhagen, Denmark, known for its cobblestone streets, canals, and many of the capital’s main cultural and architectural landmarks.
  • E. Valby
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • 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_69d8e8db5b6c8190984b61f91981f575 completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e6386f0fac819081bbc29172c8965e completed April 20, 2026, 2:30 p.m.
Created at: April 10, 2026, 1:41 p.m.