Triple

T19536875
Position Surface form Disambiguated ID Type / Status
Subject Niels Brock Copenhagen Business College E488788 entity
Predicate hasCampusIn P4623 FINISHED
Object Frederiksberg 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: Frederiksberg | Statement: [Niels Brock Copenhagen Business College, hasCampusIn, Frederiksberg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frederiksberg
Context triple: [Niels Brock Copenhagen Business College, hasCampusIn, Frederiksberg]
  • A. Frederiksberg chosen
    Frederiksberg is an affluent, centrally located municipality in Denmark that forms an enclave within the city of Copenhagen and is known for its parks, cultural institutions, and historic architecture.
  • B. Valby
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • C. Hørsholm
    Hørsholm is a suburban town in eastern Denmark, located north of Copenhagen in the Capital Region.
  • D. Hellerup
    Hellerup is a suburban district just north of central Copenhagen, known for its affluent residential areas, seaside location, and role as a key transport and commercial hub.
  • E. Favrskov
    Favrskov is a municipality in the Central Denmark Region, known for its mix of small towns, rural landscapes, and proximity to the city of Aarhus.
  • 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.