Triple

T6488099
Position Surface form Disambiguated ID Type / Status
Subject Kolsås E146564 entity
Predicate hasLandmark P105 FINISHED
Object Kolsås station E632559 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: Kolsås station | Statement: [Kolsås, hasLandmark, Kolsås station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kolsås station
Context triple: [Kolsås, hasLandmark, Kolsås station]
  • A. Kolsås station chosen
    Kolsås station is a metro terminus on the Kolsås Line of the Oslo Metro system in Bærum, Norway.
  • B. Nydalen station
    Nydalen station is an Oslo Metro station serving the Nydalen area in the Nordre Aker borough of Oslo, Norway.
  • C. Kjelsås station
    Kjelsås station is a railway station in the Kjelsås neighborhood of Oslo, Norway, serving the Gjøvik Line.
  • D. 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.
  • E. Skøyen Station
    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.
  • 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_69c0090158c08190af0df9a2348d2d52 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c06a96a4048190a28dee5fd9258486 completed March 22, 2026, 10:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c769ddf9e08190b64216fa37d6ca19 completed March 28, 2026, 5:40 a.m.
Created at: March 22, 2026, 4:52 p.m.