Triple

T7547132
Position Surface form Disambiguated ID Type / Status
Subject Rolf Gerhardsen E178433 entity
Predicate employer P7 FINISHED
Object Arbeiderbladet E19344 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: Arbeiderbladet | Statement: [Rolf Gerhardsen, employer, Arbeiderbladet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Arbeiderbladet
Context triple: [Rolf Gerhardsen, employer, Arbeiderbladet]
  • A. Arbeiderbladet chosen
    Arbeiderbladet was a prominent Norwegian daily newspaper historically affiliated with the Norwegian Labour Party and influential in shaping the country’s social-democratic discourse.
  • B. Dagbladet
    Dagbladet is a major Norwegian daily newspaper known for its liberal editorial stance and significant influence on public debate in Norway.
  • C. Aftenposten
    Aftenposten is Norway’s largest and one of its oldest daily newspapers, known for its national influence and comprehensive coverage of news, politics, and culture.
  • D. Bergens Tidende
    Bergens Tidende is a major Norwegian daily newspaper based in Bergen, known as one of the country’s leading regional papers.
  • E. Aftonbladet
    Aftonbladet is one of Sweden’s largest and most influential daily newspapers, known for its tabloid format and extensive online presence.
  • 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_69c69f2cbe08819088f9eb0c03ef529b completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f89a7b2c8190b2ca57edbb4f0390 completed March 27, 2026, 9:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84f2662f881909f65c936be9eab56 completed March 28, 2026, 9:59 p.m.
Created at: March 27, 2026, 3:49 p.m.