Triple

T23531385
Position Surface form Disambiguated ID Type / Status
Subject Gjøvik Station E576579 entity
Predicate architect P184 FINISHED
Object Paul Armin Due NE NERFINISHED

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: Paul Armin Due | Statement: [Gjøvik Station, architect, Paul Armin Due]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Armin Due
Context triple: [Gjøvik Station, architect, Paul Armin Due]
  • A. Paul Armin Due chosen
    Paul Armin Due was a Norwegian architect known for designing numerous railway stations and public buildings in Norway around the turn of the 20th century.
  • B. Fredric R. Mann
    Fredric R. Mann was an American businessman and philanthropist known for his major support of the performing arts, particularly in Philadelphia.
  • C. Kurt Kittner
    Kurt Kittner is a former American football quarterback best known for his standout collegiate career at the University of Illinois and a brief stint in the NFL, primarily with the Atlanta Falcons.
  • D. Hal Morgenstern
    Hal Morgenstern is an American epidemiologist known for his contributions to cancer epidemiology and methods in observational study design.
  • E. Guy Farley
    Guy Farley is a British film composer known for his work on a variety of feature films, television projects, and commercials.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e245f5a8848190a2ba42e271c6c31f completed April 17, 2026, 2:38 p.m.
NER Named-entity recognition batch_69f1ac78581c8190bd9d09ce2be8029d completed April 29, 2026, 7 a.m.
Created at: April 17, 2026, 6:09 p.m.