Triple

T8676924
Position Surface form Disambiguated ID Type / Status
Subject Karup E205937 entity
Predicate hasMajorFacility P105 FINISHED
Object Flyvestation Karup
Flyvestation Karup is Denmark’s largest air base and a central hub for the Royal Danish Air Force, located near the town of Karup in Jutland.
 E752092 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: Flyvestation Karup | Statement: [Karup, hasMajorFacility, Flyvestation Karup]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Flyvestation Karup
Context triple: [Karup, hasMajorFacility, Flyvestation Karup]
  • A. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • B. 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.
  • C. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • D. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • E. Koldinghus
    Koldinghus is a historic royal castle and museum in the Danish city of Kolding, known for its dramatic ruin-restoration architecture and cultural exhibitions.
  • 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: Flyvestation Karup
Triple: [Karup, hasMajorFacility, Flyvestation Karup]
Generated description
Flyvestation Karup is Denmark’s largest air base and a central hub for the Royal Danish Air Force, located near the town of Karup in Jutland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Flyvestation Karup
Target entity description: Flyvestation Karup is Denmark’s largest air base and a central hub for the Royal Danish Air Force, located near the town of Karup in Jutland.
  • A. Møllehøj
    Møllehøj is the highest natural point in Denmark, located in the hilly region of eastern Jutland.
  • B. 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.
  • C. Knudshoved
    Knudshoved is a coastal area on the Danish island of Funen that serves as a key transport hub and former ferry terminal at the western end of the Great Belt crossing.
  • D. Blangsted
    Blangsted is a surname most notably associated with Folmar Blangsted, a film editor.
  • E. Koldinghus
    Koldinghus is a historic royal castle and museum in the Danish city of Kolding, known for its dramatic ruin-restoration architecture and cultural exhibitions.
  • 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_69ca83529a9c8190b5c075b4f14636ed completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc49f67cdc819092d1ca541c6d22b9 completed March 31, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69cef3a008d48190bd0e58f615eda148 completed April 2, 2026, 10:54 p.m.
NEDg Description generation batch_69cef52000048190bc5451cfb6446ced completed April 2, 2026, 11 p.m.
NED2 Entity disambiguation (via description) batch_69cef809df548190b4f9ecc709b3b065 completed April 2, 2026, 11:13 p.m.
Created at: March 30, 2026, 6:32 p.m.