Triple

T18597044
Position Surface form Disambiguated ID Type / Status
Subject Aarhus Airport E454517 entity
Predicate operator P179 FINISHED
Object Aarhus Airport A/S 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: Aarhus Airport A/S | Statement: [Aarhus Airport, operator, Aarhus Airport A/S]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aarhus Airport A/S
Context triple: [Aarhus Airport, operator, Aarhus Airport A/S]
  • A. Aarhus Airport chosen
    Aarhus Airport is a regional international airport serving the city of Aarhus and the surrounding area in eastern Jutland, Denmark.
  • B. Copenhagen Airports A/S
    Copenhagen Airports A/S is the Danish company that owns and manages Copenhagen Airport and related airport operations in the Copenhagen area.
  • C. 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.
  • D. Midtjyllands Airport
    Midtjyllands Airport is a regional airport in central Jutland, Denmark, serving domestic and limited international flights for the surrounding Midtjylland area.
  • E. 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.
  • 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_69d8d38ae7e081908a98df1251842402 completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e5474ce0c08190b440cbe86b6ef7b9 completed April 19, 2026, 9:21 p.m.
Created at: April 10, 2026, 11:44 a.m.