Triple

T19155339
Position Surface form Disambiguated ID Type / Status
Subject Bromma E468914 entity
Predicate contains P35 FINISHED
Object Bromma 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: Bromma Airport | Statement: [Bromma, contains, Bromma Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bromma Airport
Context triple: [Bromma, contains, Bromma 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 Skavsta Airport
    Stockholm Skavsta Airport is an international low-cost airport in Sweden serving the Stockholm region, particularly known as a hub for budget airlines and charter flights.
  • C. Norrköping Airport
    Norrköping Airport is a regional airport in Norrköping, Sweden, serving domestic and limited international flights for the surrounding area.
  • D. Västerås Airport
    Västerås Airport is a regional airport in Västerås, Sweden, serving both commercial and general aviation traffic and acting as an alternative gateway to the Stockholm area.
  • E. Uppsala Airport
    Uppsala Airport is a Swedish airfield near the city of Uppsala, primarily used for military and general aviation rather than large-scale commercial passenger traffic.
  • 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_69d8dd084ff48190ac0f8c46ee722629 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5eeb914248190a92dc5f30cbc8fcc completed April 20, 2026, 9:15 a.m.
Created at: April 10, 2026, 12:06 p.m.