Triple

T13552168
Position Surface form Disambiguated ID Type / Status
Subject Aarhus University E323675 entity
Predicate hasCampus P116 FINISHED
Object Emdrup
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
E1047324 NE FINISHED

How this triple was built (4 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: Emdrup | Statement: [Aarhus University, hasCampus, Emdrup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emdrup
Context triple: [Aarhus University, hasCampus, Emdrup]
  • A. Hornbæk
    Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
  • B. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • C. Birkerød
    Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
  • D. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Emdrup
Triple: [Aarhus University, hasCampus, Emdrup]
Generated description
Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Emdrup
Target entity description: Emdrup is a district in Copenhagen, Denmark, known for hosting a campus of Aarhus University and various educational and residential facilities.
  • A. Hornbæk
    Hornbæk is a coastal town in northern Zealand, Denmark, known for its sandy beaches, holiday villas, and role as a popular seaside resort.
  • B. Rødovre
    Rødovre is a suburban municipality in the Capital Region of Denmark, located just west of central Copenhagen.
  • C. Birkerød
    Birkerød is a suburban town in northeastern Zealand, Denmark, known for its residential character, green surroundings, and proximity to Copenhagen.
  • D. Næstved
    Næstved is a historic market town and commercial center in southern Denmark, located on the island of Zealand.
  • 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. chosen

Provenance (5 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff0a6548190b8cde5084cef0061 completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f75da721208190a3f5159125dbde9a completed May 3, 2026, 2:37 p.m.
NEDg Description generation batch_69f75ec5101081909652b0c0998b36c8 completed May 3, 2026, 2:42 p.m.
NED2 Entity disambiguation (via description) batch_69f75f4a3b0c81908c0ca0351771953b completed May 3, 2026, 2:44 p.m.
Created at: April 9, 2026, 9:46 p.m.