Triple

T4670122
Position Surface form Disambiguated ID Type / Status
Subject Kongsberg E102940 entity
Predicate hasTransportation P105 FINISHED
Object Kongsberg Station
Kongsberg Station is a railway station in Kongsberg, Norway, serving as a regional transport hub on the Sørlandet Line.
 E460769 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: Kongsberg Station | Statement: [Kongsberg, hasTransportation, Kongsberg Station]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kongsberg Station
Context triple: [Kongsberg, hasTransportation, Kongsberg Station]
  • A. Arendal Station
    Arendal Station is the main railway station serving the coastal town of Arendal in Agder county, Norway.
  • B. Kongsberg
    Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
  • C. Skudeneshavn
    Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
  • D. Port of Namsos
    The Port of Namsos is a Norwegian coastal harbor serving as a regional hub for maritime transport, industry, and trade in and around the town of Namsos.
  • E. Lyngseidet
    Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
  • 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: Kongsberg Station
Triple: [Kongsberg, hasTransportation, Kongsberg Station]
Generated description
Kongsberg Station is a railway station in Kongsberg, Norway, serving as a regional transport hub on the Sørlandet Line.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kongsberg Station
Target entity description: Kongsberg Station is a railway station in Kongsberg, Norway, serving as a regional transport hub on the Sørlandet Line.
  • A. Arendal Station
    Arendal Station is the main railway station serving the coastal town of Arendal in Agder county, Norway.
  • B. Kongsberg
    Kongsberg is a Norwegian town known for its historic silver mines and its modern high-tech and defense industries.
  • C. Skudeneshavn
    Skudeneshavn is a historic coastal town in southwestern Norway known for its well-preserved wooden architecture and maritime heritage.
  • D. Port of Namsos
    The Port of Namsos is a Norwegian coastal harbor serving as a regional hub for maritime transport, industry, and trade in and around the town of Namsos.
  • E. Lyngseidet
    Lyngseidet is a small coastal village in northern Norway, known for its scenic fjord and mountain surroundings on the Lyngen Peninsula.
  • 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_69bd43d9cba4819086c1ab1c2d9d2133 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd634ef5608190925663e988e3585b completed March 20, 2026, 3:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69be0390c238819089fb54648dfe1e64 completed March 21, 2026, 2:33 a.m.
NEDg Description generation batch_69be0542daf08190b792855c8129ac50 completed March 21, 2026, 2:41 a.m.
NED2 Entity disambiguation (via description) batch_69be05c1dcd48190a08a5748e86a5ac8 completed March 21, 2026, 2:43 a.m.
Created at: March 20, 2026, 1:15 p.m.