Triple

T14057106
Position Surface form Disambiguated ID Type / Status
Subject Vanløse E338246 entity
Predicate adjacentTo P224 FINISHED
Object Valby E363201 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: Valby | Statement: [Vanløse, adjacentTo, Valby]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Valby
Context triple: [Vanløse, adjacentTo, Valby]
  • A. Valby chosen
    Valby is a district in Copenhagen, Denmark, known as an important local transport and residential area within the city.
  • B. Frederiksberg
    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.
  • 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. Hvidovre
    Hvidovre is a suburban municipality in the Capital Region of Denmark, located just southwest of central Copenhagen.
  • E. Ennore
    Ennore is a coastal industrial and port suburb in the northern part of Chennai, Tamil Nadu, India.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8e6d008190af8892f34c5cefbd completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb710b34819094e3387a3ef6fcff completed May 8, 2026, 3:04 p.m.
Created at: April 9, 2026, 10:20 p.m.