Triple

T205516
Position Surface form Disambiguated ID Type / Status
Subject University of Oslo E4601 entity
Predicate hasNotableAlumni P51 FINISHED
Object Jonas Gahr Støre E19343 NE FINISHED

How this triple was built (2 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: Jonas Gahr Støre | Statement: [University of Oslo, hasNotableAlumni, Jonas Gahr Støre]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jonas Gahr Støre
Context triple: [University of Oslo, hasNotableAlumni, Jonas Gahr Støre]
  • A. Jonas Gahr Støre chosen
    Jonas Gahr Støre is a Norwegian politician who has served as Prime Minister of Norway and is a leading figure in the country’s centre-left politics.
  • B. Jens Stoltenberg
    Jens Stoltenberg is a Norwegian politician who served as Norway’s prime minister and later became the secretary general of NATO.
  • C. Håkon Wium Lie
    Håkon Wium Lie is a Norwegian web pioneer best known as the creator of Cascading Style Sheets (CSS) and a key figure in the development of open web standards.
  • D. Tonje Brenna
    Tonje Brenna is a Norwegian politician from the Labour Party who has held prominent leadership roles and served as a government minister.
  • E. Ragnhild Lie
    Ragnhild Lie is a Norwegian given name bearer, likely known as a woman from Norway with the surname Lie, though specific public details about her are limited.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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.
Created at: Feb. 28, 2026, 2:51 a.m.