Triple

T2006127
Position Surface form Disambiguated ID Type / Status
Subject Rector of the University of Oslo E43589 entity
Predicate officeHeldBy P537 FINISHED
Object Svein Stølen
Svein Stølen is a Norwegian chemist and academic leader who serves as the rector of the University of Oslo.
E230448 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: Svein Stølen | Statement: [Rector of the University of Oslo, officeHeldBy, Svein Stølen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Svein Stølen
Context triple: [Rector of the University of Oslo, officeHeldBy, Svein Stølen]
  • A. Trond Giaever
    Trond Giaever is the child of Norwegian-American physicist and Nobel laureate Ivar Giaever.
  • B. Geir Karlsen
    Geir Karlsen is a Norwegian business executive best known for leading the low-cost airline Norwegian Air Shuttle through a major financial restructuring and recovery.
  • C. Morten Lie
    Morten Lie is a person notable enough to be recognized as a bearer of the surname Lie, though specific widely known public details about him are limited.
  • D. Kjell Lie
    Kjell Lie is a person notable enough to be recognized as a bearer of the surname Lie, though specific widely known public details about him are limited.
  • E. Sjur Lie
    Sjur Lie is a Norwegian mathematician known for his contributions to differential geometry and the theory of Lie groups.
  • 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: Svein Stølen
Triple: [Rector of the University of Oslo, officeHeldBy, Svein Stølen]
Generated description
Svein Stølen is a Norwegian chemist and academic leader who serves as the rector of the University of Oslo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Svein Stølen
Target entity description: Svein Stølen is a Norwegian chemist and academic leader who serves as the rector of the University of Oslo.
  • A. Trond Giaever
    Trond Giaever is the child of Norwegian-American physicist and Nobel laureate Ivar Giaever.
  • B. Geir Karlsen
    Geir Karlsen is a Norwegian business executive best known for leading the low-cost airline Norwegian Air Shuttle through a major financial restructuring and recovery.
  • C. Morten Lie
    Morten Lie is a person notable enough to be recognized as a bearer of the surname Lie, though specific widely known public details about him are limited.
  • D. Kjell Lie
    Kjell Lie is a person notable enough to be recognized as a bearer of the surname Lie, though specific widely known public details about him are limited.
  • E. Sjur Lie
    Sjur Lie is a Norwegian mathematician known for his contributions to differential geometry and the theory of Lie groups.
  • 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_69a88715dbbc8190b2299e29e955d997 completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb898795481909920c1a4c4d62c2d completed March 7, 2026, 5:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae2707c074819095f932a67f7b5fb9 completed March 9, 2026, 1:48 a.m.
NEDg Description generation batch_69ae279ffb288190b61d9e59db026f59 completed March 9, 2026, 1:51 a.m.
NED2 Entity disambiguation (via description) batch_69ae2848b40c819093ea338b7a940586 completed March 9, 2026, 1:54 a.m.
Created at: March 4, 2026, 7:37 p.m.