Triple

T9421814
Position Surface form Disambiguated ID Type / Status
Subject From Day to Day E227170 entity
Predicate author P4 FINISHED
Object Odd Nansen E43592 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: Odd Nansen | Statement: [From Day to Day, author, Odd Nansen]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odd Nansen
Context triple: [From Day to Day, author, Odd Nansen]
  • A. Odd Nansen chosen
    Odd Nansen was a Norwegian architect, humanitarian, and diarist known for his detailed accounts of life in Nazi concentration camps during World War II.
  • B. Nellallitea Larsen
    Nellallitea Larsen was an American novelist and key figure of the Harlem Renaissance, best known for her works exploring race, identity, and gender such as "Passing" and "Quicksand."
  • C. Hjalmar Christensen
    Hjalmar Christensen was a Norwegian writer, literary critic, and professor known for his contributions to early 20th-century Norwegian literature and cultural debate.
  • D. Gunnbjørn Fjeldt
    Gunnbjørn Fjeldt is the highest mountain in Greenland and the entire Arctic, located in the Watkins Range of eastern Greenland.
  • E. Viktor E. Viking
    Viktor E. Viking is the costumed Viking warrior who serves as the official mascot and spirited symbol of Portland State University's athletic teams, especially its football program.
  • 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_69ca84359e7c819091148ba4b670e436 completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd6c2651c48190808281779fab49df completed April 1, 2026, 7:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69d107d290148190855b8d50eb80c591 completed April 4, 2026, 12:45 p.m.
Created at: March 30, 2026, 7:48 p.m.