Triple

T2230069
Position Surface form Disambiguated ID Type / Status
Subject SAS Ireland E48743 entity
Predicate focusCity P164 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: [SAS Ireland, focusCity, Stockholm Arlanda Airport]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Stockholm Arlanda Airport
Context triple: [SAS Ireland, focusCity, 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. Gothenburg City Airport
    Gothenburg City Airport is a regional airport serving the Gothenburg area in western Sweden.
  • E. Arlanda Central Station
    Arlanda Central Station is the main railway station serving Stockholm Arlanda Airport, connecting the airport to regional and long-distance train services in 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_69a88aa51b388190949868ec9766e587 completed March 4, 2026, 7:40 p.m.
NER Named-entity recognition batch_69abc069e0ac8190bcda8cba9f5c7a5d completed March 7, 2026, 6:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae6b001ee481909b28aea25ad7b906 completed March 9, 2026, 6:38 a.m.
Created at: March 4, 2026, 7:47 p.m.