Triple

T7655881
Position Surface form Disambiguated ID Type / Status
Subject Skøyen E173379 entity
Predicate hasTransportNode P2413 FINISHED
Object Skøyen Station E622960 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: Skøyen Station | Statement: [Skøyen, hasTransportNode, Skøyen Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Skøyen Station
Context triple: [Skøyen, hasTransportNode, Skøyen Station]
  • A. Skøyen Station chosen
    Skøyen Station is a major railway and commuter hub in Oslo, Norway, serving regional and local trains as part of the city's western transport corridor.
  • B. Lysaker Station
    Lysaker Station is a major railway station in the Oslo metropolitan area of Norway, serving as an important commuter and regional transport hub.
  • C. Frognerseteren station
    Frognerseteren station is a terminal Oslo Metro station located in the Frognerseteren area, known for its scenic surroundings and access to hiking and skiing trails.
  • D. Nydalen station
    Nydalen station is an Oslo Metro station serving the Nydalen area in the Nordre Aker borough of Oslo, Norway.
  • E. Drammen Station
    Drammen Station is a major railway hub in Drammen, Norway, connecting regional and long-distance train services to Oslo and other parts of the country.
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c7018ea3688190907c3ac7d25e3da6 completed March 27, 2026, 10:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9494351488190852b600d9666d1eb completed March 29, 2026, 3:46 p.m.
Created at: March 27, 2026, 3:59 p.m.