Triple

T205489
Position Surface form Disambiguated ID Type / Status
Subject University of Oslo E4601 entity
Predicate hasCampus P116 FINISHED
Object Blindern
Blindern is the main campus area of the University of Oslo, housing many of its central academic buildings and facilities.
 E3654 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: Blindern | Statement: [University of Oslo, hasCampus, Blindern]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Blindern
Context triple: [University of Oslo, hasCampus, Blindern]
  • A. Oslo
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • D. Lysgårdsbakken
    Lysgårdsbakken is a large ski jumping hill complex in Lillehammer, Norway, best known for hosting the ski jumping events of the 1994 Winter Olympics.
  • E. Bygdøy Royal Estate
    Bygdøy Royal Estate is a historic royal property on the Bygdøy peninsula in Oslo that serves as one of the official residences of Norway’s monarch.
  • 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: Blindern
Triple: [University of Oslo, hasCampus, Blindern]
Generated description
Blindern is the main campus area of the University of Oslo, housing many of its central academic buildings and facilities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Blindern
Target entity description: Blindern is the main campus area of the University of Oslo, housing many of its central academic buildings and facilities.
  • A. Oslo chosen
    Oslo is the capital and largest city of Norway, known as a major cultural, economic, and governmental center.
  • B. Lillehammer
    Lillehammer is a Norwegian town in the Gudbrandsdalen valley, best known internationally for staging the 1994 Winter Olympics.
  • C. Arendal
    Arendal is a coastal town and municipality in southern Norway known historically as a regional political and trading center.
  • D. Lysgårdsbakken
    Lysgårdsbakken is a large ski jumping hill complex in Lillehammer, Norway, best known for hosting the ski jumping events of the 1994 Winter Olympics.
  • E. Bygdøy Royal Estate
    Bygdøy Royal Estate is a historic royal property on the Bygdøy peninsula in Oslo that serves as one of the official residences of Norway’s monarch.
  • F. None of above.

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_69a25737567c81908f9c505300239181 completed Feb. 28, 2026, 2:47 a.m.
NER Named-entity recognition batch_69a25c04e42481909e957cb34dc02731 completed Feb. 28, 2026, 3:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69a32f29799c8190a445a231006bf436 completed Feb. 28, 2026, 6:08 p.m.
NEDg Description generation batch_69a32f866fd4819097e93255723602cc completed Feb. 28, 2026, 6:10 p.m.
NED2 Entity disambiguation (via description) batch_69a32fe4faf88190a3637cbfc768522e completed Feb. 28, 2026, 6:11 p.m.
Created at: Feb. 28, 2026, 2:51 a.m.