Triple

T20647996
Position Surface form Disambiguated ID Type / Status
Subject Crown Princess Märtha of Norway E507408 entity
Predicate givenName P17 FINISHED
Object Märtha 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: Märtha | Statement: [Crown Princess Märtha of Norway, givenName, Märtha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Märtha
Context triple: [Crown Princess Märtha of Norway, givenName, Märtha]
  • A. Märtha chosen
    Märtha was a Swedish princess and Crown Princess of Norway, known for her humanitarian work and influential role during World War II.
  • B. Margarete
    Margarete is a female given name of Greek origin, commonly associated with the meaning "pearl" and used in various European languages.
  • C. Christa
    Christa was the first name of Christa McAuliffe, the American teacher and astronaut selected as the first private citizen to fly in space.
  • D. Maddalene
    Maddalene is a feminine given name, typically considered a variant of Maddalena or Magdalene, with roots in Christian and European naming traditions.
  • E. Mary Frank
    Mary Frank is an American artist known for her expressive sculptures, paintings, and prints that often explore themes of nature, myth, and the human figure.
  • 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_69e0b4be702c8190a3d2410a881d310a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6af1fbfa881908a5b9db143e362d0 completed April 20, 2026, 10:56 p.m.
Created at: April 16, 2026, 11:43 a.m.