Triple

T15409366
Position Surface form Disambiguated ID Type / Status
Subject Indre By E368543 entity
Predicate contains P35 FINISHED
Object Christianshavn E343076 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: Christianshavn | Statement: [Indre By, contains, Christianshavn]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Christianshavn
Context triple: [Indre By, contains, Christianshavn]
  • A. Christianshavn chosen
    Christianshavn is a historic, canal-filled neighborhood in central Copenhagen known for its maritime atmosphere, colorful houses, and alternative cultural scene.
  • B. Ennore
    Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
  • C. 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.
  • D. Nordhavn
    Nordhavn is a harbor-side district in Copenhagen, Denmark, known for its large-scale urban redevelopment into a modern, sustainable waterfront neighborhood.
  • E. Hvidovre
    Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
  • 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_69d85a16c68c819099c1b547fbc87b32 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03ea4f13c819085d26fd32b5dca6f completed April 16, 2026, 1:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ffb0319f248190a37c9afa09c32428 completed May 9, 2026, 10:07 p.m.
Created at: April 10, 2026, 3:20 a.m.