Triple

T3506307
Position Surface form Disambiguated ID Type / Status
Subject Bergen E74082 entity
Predicate hasAirport P105 FINISHED
Object Bergen Airport, Flesland E160361 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: Bergen Airport, Flesland | Statement: [Bergen, hasAirport, Bergen Airport, Flesland]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bergen Airport, Flesland
Context triple: [Bergen, hasAirport, Bergen Airport, Flesland]
  • A. Bergen Airport, Flesland chosen
    Bergen Airport, Flesland is the main international airport serving the city of Bergen and western Norway, handling both domestic and international flights.
  • B. Oslo Airport, Gardermoen
    Oslo Airport, Gardermoen is Norway’s main international airport and the primary aviation hub serving the Oslo region.
  • C. Trondheim Airport, Værnes
    Trondheim Airport, Værnes is a major international airport in central Norway serving the city of Trondheim and the surrounding Trøndelag region.
  • D. Stavanger Airport, Sola
    Stavanger Airport, Sola is a major international airport in southwestern Norway serving the Stavanger region and the North Sea oil industry.
  • E. Tromsø Airport, Langnes
    Tromsø Airport, Langnes is a major regional and international airport in northern Norway serving the city of Tromsø and the surrounding Arctic region.
  • 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbf52bd8819085a2ac5f48cc5c68 completed March 8, 2026, 6:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69b37e6aea8c81908dbe4748dd8a9d9c completed March 13, 2026, 3:03 a.m.
Created at: March 8, 2026, 3:18 p.m.