Triple

T8676948
Position Surface form Disambiguated ID Type / Status
Subject Karup E205937 entity
Predicate hasAirportName P4100 FINISHED
Object Midtjyllands Airport E712817 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: Midtjyllands Airport | Statement: [Karup, hasAirportName, Midtjyllands Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Midtjyllands Airport
Context triple: [Karup, hasAirportName, Midtjyllands Airport]
  • A. Midtjyllands Airport chosen
    Midtjyllands Airport is a regional airport in central Jutland, Denmark, serving domestic and limited international flights for the surrounding Midtjylland area.
  • B. Esbjerg Airport
    Esbjerg Airport is a regional airport in western Denmark that primarily serves domestic flights and offshore oil and gas industry traffic in the North Sea.
  • C. Bornholm Airport
    Bornholm Airport is the main regional airport serving the Danish island of Bornholm, providing domestic and limited international connections.
  • D. Aarhus Airport
    Aarhus Airport is a regional international airport serving the city of Aarhus and the surrounding area in eastern Jutland, Denmark.
  • E. Aalborg Airport
    Aalborg Airport is an international airport in northern Denmark serving the city of Aalborg and the surrounding region with domestic and European flights.
  • 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_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.
Created at: March 30, 2026, 6:32 p.m.