Triple

T4959926
Position Surface form Disambiguated ID Type / Status
Subject Swedavia E111378 entity
Predicate owns P347 FINISHED
Object Bromma Stockholm Airport E19491 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: Bromma Stockholm Airport | Statement: [Swedavia, owns, Bromma Stockholm Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bromma Stockholm Airport
Context triple: [Swedavia, owns, Bromma Stockholm Airport]
  • A. Stockholm Bromma Airport chosen
    Stockholm Bromma Airport is a regional airport near central Stockholm, Sweden, primarily serving domestic and short-haul European flights.
  • B. Stockholm Arlanda Airport
    Stockholm Arlanda Airport is Sweden’s largest and busiest international airport, serving as the primary gateway to Stockholm and a major hub for Scandinavian and European air traffic.
  • C. Gothenburg Landvetter Airport
    Gothenburg Landvetter Airport is the main international airport serving the Gothenburg region in western Sweden.
  • D. Malmö Airport
    Malmö Airport is an international airport in southern Sweden serving the city of Malmö and the wider Øresund Region, including nearby parts of Denmark.
  • E. Gustaf III Airport
    Gustaf III Airport is the small, short-runway airport serving the Caribbean island of Saint Barthélemy, known for its challenging approach and dramatic landings close to a beach.
  • 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_69bd4418390c8190b7e9766a2512ce55 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71da80008190a0d606d5091822b8 completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf10b0ec0c8190bcd4503dd09667c7 completed March 21, 2026, 9:42 p.m.
Created at: March 20, 2026, 1:32 p.m.