Triple

T21739922
Position Surface form Disambiguated ID Type / Status
Subject Berne E536626 entity
Predicate hasAirport P105 FINISHED
Object Bern Airport 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: Bern Airport | Statement: [Berne, hasAirport, Bern Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bern Airport
Context triple: [Berne, hasAirport, Bern Airport]
  • A. Bern Airport chosen
    Bern Airport is a small regional airport in Switzerland serving the city of Bern and offering domestic and limited international flights.
  • B. Copenhagen Airport Kastrup
    Copenhagen Airport Kastrup is Denmark’s largest and busiest international airport, serving as the main air hub for Copenhagen and much of Scandinavia.
  • C. Hans Christian Andersen Airport
    Hans Christian Andersen Airport is a regional airport serving the city of Odense on the island of Funen in Denmark.
  • 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. Bost Airport
    Bost Airport is a regional airport serving the city of Lashkargah in Helmand Province, Afghanistan.
  • 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_69e0c46df5448190b4322127ffc4c690 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69f01a714c208190b96efe23ed3bf0db completed April 28, 2026, 2:24 a.m.
Created at: April 16, 2026, 6:49 p.m.