Triple

T7394589
Position Surface form Disambiguated ID Type / Status
Subject Oslo Metro Line 1 E170589 entity
Predicate hasStation P35 FINISHED
Object Holmenkollen station
Holmenkollen station is a metro stop in Oslo, Norway, serving the hillside area near the famous Holmenkollen ski jump and recreational trails.
E661130 NE FINISHED

How this triple was built (4 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: Holmenkollen station | Statement: [Oslo Metro Line 1, hasStation, Holmenkollen station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Holmenkollen station
Context triple: [Oslo Metro Line 1, hasStation, Holmenkollen station]
  • A. 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.
  • B. Nydalen station
    Nydalen station is an Oslo Metro station serving the Nydalen area in the Nordre Aker borough of Oslo, Norway.
  • C. Kolsås station
    Kolsås station is a metro terminus on the Kolsås Line of the Oslo Metro system in Bærum, Norway.
  • D. 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.
  • 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. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Holmenkollen station
Triple: [Oslo Metro Line 1, hasStation, Holmenkollen station]
Generated description
Holmenkollen station is a metro stop in Oslo, Norway, serving the hillside area near the famous Holmenkollen ski jump and recreational trails.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Holmenkollen station
Target entity description: Holmenkollen station is a metro stop in Oslo, Norway, serving the hillside area near the famous Holmenkollen ski jump and recreational trails.
  • A. 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.
  • B. Nydalen station
    Nydalen station is an Oslo Metro station serving the Nydalen area in the Nordre Aker borough of Oslo, Norway.
  • C. Kolsås station
    Kolsås station is a metro terminus on the Kolsås Line of the Oslo Metro system in Bærum, Norway.
  • D. 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.
  • 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. chosen

Provenance (5 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f2279de4819081b8876d02f55388 completed March 27, 2026, 9:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69c810fcb1408190a6ed22213bd7830b completed March 28, 2026, 5:33 p.m.
NEDg Description generation batch_69c8119611148190ae72e52242798dfe completed March 28, 2026, 5:36 p.m.
NED2 Entity disambiguation (via description) batch_69c8121126e08190a95ab570569158cf completed March 28, 2026, 5:38 p.m.
Created at: March 27, 2026, 3:09 p.m.