Triple

T14100725
Position Surface form Disambiguated ID Type / Status
Subject Øresund Line E339371 entity
Predicate hasStation P35 FINISHED
Object Hyllie station E1074670 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: Hyllie station | Statement: [Øresund Line, hasStation, Hyllie station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hyllie station
Context triple: [Øresund Line, hasStation, Hyllie station]
  • A. Hyllie station chosen
    Hyllie station is a major railway and transport hub in Malmö, Sweden, serving regional and international trains as well as local transit connections.
  • B. Storo station
    Storo station is a major interchange stop in Oslo, Norway, connecting metro, tram, and bus services in the Storo/Nydalen area.
  • C. Strømmen Station
    Strømmen Station is a railway station serving the town of Strømmen in Viken county, Norway, on the Oslo commuter rail network.
  • D. Syosset station
    Syosset station is a Long Island Rail Road commuter rail stop serving the community of Syosset in Nassau County, New York.
  • E. Linderud station
    Linderud station is an Oslo Metro stop in the Linderud neighborhood, providing urban rail access on the city's east side.
  • 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_69d81c69b5c8819094aa1abf18302908 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de5fba7c10819095b1299b7b4f0310 completed April 14, 2026, 3:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf02638881908eff75453b6a2aab completed May 7, 2026, 6:50 p.m.
Created at: April 9, 2026, 10:22 p.m.