Triple

T8528462
Position Surface form Disambiguated ID Type / Status
Subject Aalborg E201878 entity
Predicate hasAirport P105 FINISHED
Object Aalborg Airport E251232 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: Aalborg Airport | Statement: [Aalborg, hasAirport, Aalborg Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aalborg Airport
Context triple: [Aalborg, hasAirport, Aalborg Airport]
  • A. Aalborg Airport chosen
    Aalborg Airport is an international airport in northern Denmark serving the city of Aalborg and the surrounding region with domestic and European flights.
  • 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. Aarhus Airport
    Aarhus Airport is a regional international airport serving the city of Aarhus and the surrounding area in eastern Jutland, Denmark.
  • D. Bornholm Airport
    Bornholm Airport is the main regional airport serving the Danish island of Bornholm, providing domestic and limited international connections.
  • E. Midtjyllands Airport
    Midtjyllands Airport is a regional airport in central Jutland, Denmark, serving domestic and limited international flights for the surrounding Midtjylland area.
  • 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_69ca83228b24819085d22e7dc99f5d94 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe672e0588190a84328e1bf974f08 completed March 31, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce6d54ef908190970a1010c8018abd completed April 2, 2026, 1:21 p.m.
Created at: March 30, 2026, 6:17 p.m.