Triple

T10824743
Position Surface form Disambiguated ID Type / Status
Subject Frederiksberg E255466 entity
Predicate hasMetroStation P522 FINISHED
Object Lindevang Station
Lindevang Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
 E890892 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: Lindevang Station | Statement: [Frederiksberg, hasMetroStation, Lindevang Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Lindevang Station
Context triple: [Frederiksberg, hasMetroStation, Lindevang Station]
  • A. Værnes Station
    Værnes Station is a railway station in Stjørdal, Norway, serving passengers traveling to and from Trondheim Airport, Værnes.
  • B. Hokksund Station
    Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
  • C. Henriksdal station
    Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
  • D. Veitvet station
    Veitvet station is a metro stop in Oslo, Norway, located in the Veitvet neighborhood and forming part of the city's rapid transit network.
  • E. Rødtvet station
    Rødtvet station is a metro stop in Oslo, Norway, located in the Grorud district and integrated into the city's rapid transit network.
  • 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: Lindevang Station
Triple: [Frederiksberg, hasMetroStation, Lindevang Station]
Generated description
Lindevang Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Lindevang Station
Target entity description: Lindevang Station is a Copenhagen Metro station serving the Frederiksberg district of Copenhagen, Denmark.
  • A. Værnes Station
    Værnes Station is a railway station in Stjørdal, Norway, serving passengers traveling to and from Trondheim Airport, Værnes.
  • B. Hokksund Station
    Hokksund Station is a railway station in Hokksund, Norway, serving as a local and regional transport hub on the country’s rail network.
  • C. Henriksdal station
    Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
  • D. Veitvet station
    Veitvet station is a metro stop in Oslo, Norway, located in the Veitvet neighborhood and forming part of the city's rapid transit network.
  • E. Rødtvet station
    Rødtvet station is a metro stop in Oslo, Norway, located in the Grorud district and integrated into the city's rapid transit network.
  • 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d734d0389c819090a892693c4046ed completed April 9, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69dff7c45f288190a5235b5d7000a32c completed April 15, 2026, 8:40 p.m.
NEDg Description generation batch_69e0026e7900819087327db5f625169c completed April 15, 2026, 9:26 p.m.
NED2 Entity disambiguation (via description) batch_69e0057a7704819096becb74dc261883 completed April 15, 2026, 9:39 p.m.
Created at: April 8, 2026, 9:19 p.m.