Triple

T1139708
Position Surface form Disambiguated ID Type / Status
Subject Oslo Tramway E23420 entity
Predicate serves P98 FINISHED
Object Bekkestua
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
 E164673 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: Bekkestua | Statement: [Oslo Tramway, serves, Bekkestua]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bekkestua
Context triple: [Oslo Tramway, serves, Bekkestua]
  • A. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • B. Bolnes
    Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
  • C. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • D. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • E. Bjørvika
    Bjørvika is a waterfront neighborhood in central Oslo, Norway, known for its modern architecture and cultural institutions such as the Munch Museum and the Oslo Opera House.
  • 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: Bekkestua
Triple: [Oslo Tramway, serves, Bekkestua]
Generated description
Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bekkestua
Target entity description: Bekkestua is a suburban center in Bærum, Norway, functioning as a local commercial and transport hub just west of Oslo.
  • A. Mortensrud
    Mortensrud is a residential neighborhood in the Søndre Nordstrand borough of Oslo, Norway, known for its multicultural population and modern church, and served as the terminus of an Oslo Metro line.
  • B. Bolnes
    Bolnes is a Dutch surname most notably associated with Catharina Bolnes, the wife of painter Johannes Vermeer.
  • C. Verdal
    Verdal is a municipality in central Norway known for its agricultural landscape, industrial activity, and the historic battlefield of Stiklestad.
  • D. Gaustad
    Gaustad is a district in Oslo, Norway, known for hosting major academic and research institutions, including parts of the University of Oslo campus.
  • E. Bjørvika
    Bjørvika is a waterfront neighborhood in central Oslo, Norway, known for its modern architecture and cultural institutions such as the Munch Museum and the Oslo Opera House.
  • 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_69a493ef399c8190b04b9146d2314f59 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4bc27c88881909c64ec30b7f66575 completed March 1, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad089d492881909c6ef4519c087386 completed March 8, 2026, 5:26 a.m.
NEDg Description generation batch_69ad0949cdf88190977da43dd53c72e0 completed March 8, 2026, 5:29 a.m.
NED2 Entity disambiguation (via description) batch_69ad09af636c81909d6bf5d65591624e completed March 8, 2026, 5:31 a.m.
Created at: March 1, 2026, 7:44 p.m.