Triple

T14109732
Position Surface form Disambiguated ID Type / Status
Subject Svanemøllen E339601 entity
Predicate locatedNear P294 FINISHED
Object Nordhavn E1111376 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: Nordhavn | Statement: [Svanemøllen, locatedNear, Nordhavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nordhavn
Context triple: [Svanemøllen, locatedNear, Nordhavn]
  • A. Nordhavn chosen
    Nordhavn is a harbor-side district in Copenhagen, Denmark, known for its large-scale urban redevelopment into a modern, sustainable waterfront neighborhood.
  • B. Sydhavn
    Sydhavn is a district in Copenhagen, Denmark, known for its former industrial harbor areas now undergoing redevelopment into residential and commercial neighborhoods.
  • C. Christianshavn
    Christianshavn is a historic, canal-filled neighborhood in central Copenhagen known for its maritime atmosphere, colorful houses, and alternative cultural scene.
  • D. Amaliehaven
    Amaliehaven is a small waterfront park and fountain garden in central Copenhagen, known for its formal design and views of the harbor and Amalienborg Palace.
  • E. Gentofte
    Gentofte is a suburban municipality just north of central Copenhagen in eastern Denmark, known for its affluent residential areas and proximity to the Øresund coast.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de600caf308190ab6d8451ed4e3797 completed April 14, 2026, 3:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69febfcd67f081909f97bcf38d814a13 completed May 9, 2026, 5:02 a.m.
Created at: April 9, 2026, 10:22 p.m.