Triple

T22111948
Position Surface form Disambiguated ID Type / Status
Subject Charlottenlund E546438 entity
Predicate nearbyArea P2064 FINISHED
Object Ordrup 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: Ordrup | Statement: [Charlottenlund, nearbyArea, Ordrup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ordrup
Context triple: [Charlottenlund, nearbyArea, Ordrup]
  • A. Felsted
    Felsted is a village in Essex, England, known for its historic independent boarding school and rural setting.
  • B. Emdrup chosen
    Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
  • C. Hornbæk
    Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
  • D. Ginnerup
    Ginnerup is a small village in Denmark best known as the birthplace of former Danish Prime Minister and NATO Secretary General Anders Fogh Rasmussen.
  • E. Ringsted
    Ringsted is a historic market town and transport hub located in the central part of the Danish island of Zealand.
  • 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_69e11e38b3848190ac3a4fa97d56e65a completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12949cc7881908898ca7dc130f57f completed April 28, 2026, 9:40 p.m.
Created at: April 16, 2026, 8:31 p.m.