Triple

T16123203
Position Surface form Disambiguated ID Type / Status
Subject Irma von Cube E391196 entity
Predicate name P16 FINISHED
Object Irma von Cube E391196 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: Irma von Cube | Statement: [Irma von Cube, name, Irma von Cube]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Irma von Cube
Context triple: [Irma von Cube, name, Irma von Cube]
  • A. Irma von Cube chosen
    Irma von Cube was a German-American screenwriter best known for her Academy Award–nominated work on the 1948 film "Johnny Belinda."
  • B. Ursula Mamlok
    Ursula Mamlok was a German-American composer known for her refined, modernist chamber and orchestral works that often employed serial techniques with expressive lyricism.
  • C. Ursula Karven
    Ursula Karven is a German actress, model, and yoga instructor known for her roles in German television series and films as well as for her popular yoga books and DVDs.
  • D. Julie von Webenau
    Julie von Webenau was a 19th-century Austrian pianist and composer known for her salon pieces and connections with prominent Romantic-era musicians.
  • E. Gui Bonsiepe
    Gui Bonsiepe is a German designer, design theorist, and educator known for his influential work in interface and information design and his contributions to design education, particularly in Latin America.
  • 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_69d87f1bb0988190b490d273dbf3fd03 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e202027e78819091192aa62aedde13 completed April 17, 2026, 9:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff2a9db848190bafb959bd7511246 completed May 10, 2026, 2:51 a.m.
Created at: April 10, 2026, 5 a.m.