Triple

T19248567
Position Surface form Disambiguated ID Type / Status
Subject Hallonbergen metro station E481326 entity
Predicate line P1293 FINISHED
Object Blue Line — NE NERFINISHED

How this triple was built (3 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: Blue Line | Statement: [Hallonbergen metro station, line, Blue Line]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blue Line
Context triple: [Hallonbergen metro station, line, Blue Line]
  • A. Blue Line
    The Blue Line is one of the color-coded rapid transit routes in the Washington Metro system, running through key parts of Washington, D.C. and its Virginia suburbs.
  • B. Blue Line
    The Blue Line is a primary light rail route of the San Diego Trolley system, running through key corridors of the San Diego metropolitan area.
  • C. Blue Line
    The Blue Line is one of the aerial cable car routes in La Paz–El Alto’s Mi Teleférico urban transit system, providing high-altitude public transportation across the Bolivian cities.
  • D. Blue Line
    The Blue Line is a light rail service in Pittsburgh's public transit system that connects downtown with several southern suburbs.
  • E. Blue Line
    The Blue Line is one of the automated people-mover routes in San Francisco International Airport’s AirTrain system, circulating between terminals, parking garages, and other key airport facilities.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blue Line
Target entity description: Blue Line is one of the main lines of the Stockholm metro system, serving several northern and western suburbs of the city.
  • A. Blue Line
    The Blue Line is one of the main lines of the Lisbon Metro system, serving key central and northern areas of Portugal’s capital city.
  • B. Blue Line
    The Blue Line is one of the major corridors of the Delhi Metro rapid transit system, connecting key residential and commercial areas across Delhi and its neighboring regions.
  • C. Blue Line
    Blue Line is the common name for Taipei Metro’s Bannan Line, a major east–west rapid transit route serving key commercial and residential districts in Taipei and New Taipei City.
  • D. Blue Line
    The Blue Line is one of the primary light rail transit routes in Calgary's CTrain system, serving key corridors across the city.
  • E. Blue Line
    The Blue Line is one of the main corridors of the Chennai Metro rapid transit system, connecting key areas of Chennai, India.
  • F. None of above. chosen

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_69d8e8cd9d1081908a181d02b88b59b8 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e5fb2e7cf881908dafd45d7a305c52 completed April 20, 2026, 10:08 a.m.
Created at: April 10, 2026, 1:27 p.m.