Triple

T14056726
Position Surface form Disambiguated ID Type / Status
Subject M1 (Copenhagen Metro) E338237 entity
Predicate hasStation P35 FINISHED
Object DR Byen station
DR Byen station is a Copenhagen Metro station serving the DR Byen media complex and surrounding areas on the M1 line.
E1094148 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: DR Byen station | Statement: [M1 (Copenhagen Metro), hasStation, DR Byen station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DR Byen station
Context triple: [M1 (Copenhagen Metro), hasStation, DR Byen station]
  • A. Henriksdal station
    Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
  • B. Vanløse station
    Vanløse station is a major public transport hub in Copenhagen that serves as an interchange between the S-train network and the Copenhagen Metro.
  • C. Midtstuen station
    Midtstuen station is a stop on Oslo’s Holmenkollen Line of the Oslo Metro, serving the hillside residential areas northwest of the city center.
  • D. Frederiksberg Station
    Frederiksberg Station is a key Copenhagen Metro and S-train interchange located in the Frederiksberg district of Denmark’s capital.
  • 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: DR Byen station
Triple: [M1 (Copenhagen Metro), hasStation, DR Byen station]
Generated description
DR Byen station is a Copenhagen Metro station serving the DR Byen media complex and surrounding areas on the M1 line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: DR Byen station
Target entity description: DR Byen station is a Copenhagen Metro station serving the DR Byen media complex and surrounding areas on the M1 line.
  • A. Henriksdal station
    Henriksdal station is a commuter rail stop in the Stockholm area that serves passengers on the Saltsjöbanan line.
  • B. Vanløse station
    Vanløse station is a major public transport hub in Copenhagen that serves as an interchange between the S-train network and the Copenhagen Metro.
  • C. Midtstuen station
    Midtstuen station is a stop on Oslo’s Holmenkollen Line of the Oslo Metro, serving the hillside residential areas northwest of the city center.
  • D. Frederiksberg Station
    Frederiksberg Station is a key Copenhagen Metro and S-train interchange located in the Frederiksberg district of Denmark’s capital.
  • 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_69d81c67ba6c819091935650dfb3b895 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de3c8e6d008190af8892f34c5cefbd completed April 14, 2026, 1:09 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd466febb88190986eb8f033d29279 completed May 8, 2026, 2:12 a.m.
NEDg Description generation batch_69fd47fa764c8190b1d691f5847b7a05 completed May 8, 2026, 2:18 a.m.
NED2 Entity disambiguation (via description) batch_69fd492226888190a014b23e506ab19c completed May 8, 2026, 2:23 a.m.
Created at: April 9, 2026, 10:20 p.m.