Triple

T4688779
Position Surface form Disambiguated ID Type / Status
Subject ESSA E103983 entity
Predicate airportName P4100 FINISHED
Object Stockholm Arlanda Airport E18898 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: Stockholm Arlanda Airport | Statement: [ESSA, airportName, Stockholm Arlanda Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stockholm Arlanda Airport
Context triple: [ESSA, airportName, Stockholm Arlanda Airport]
  • A. Stockholm Arlanda Airport chosen
    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.
  • B. Stockholm Bromma Airport
    Stockholm Bromma Airport is a regional airport near central Stockholm, Sweden, primarily serving domestic and short-haul European flights.
  • 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. Gothenburg City Airport
    Gothenburg City Airport is a regional airport serving the Gothenburg area in western Sweden.
  • 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_69bd43df91f481908e9add1b617b60ef completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd6399621881909aa8ffb1c27284e9 completed March 20, 2026, 3:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c84eb4481908a7188672624bc4d completed March 21, 2026, 8:53 a.m.
Created at: March 20, 2026, 1:16 p.m.