Triple

T12568944
Position Surface form Disambiguated ID Type / Status
Subject Johanna Leonberger E295547 entity
Predicate givenName P17 FINISHED
Object Johanna E103810 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: Johanna | Statement: [Johanna Leonberger, givenName, Johanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johanna
Context triple: [Johanna Leonberger, givenName, Johanna]
  • A. Johanna chosen
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • B. Johanna
    "Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
  • C. Johanna
    Johanna is the birth name of Magda Goebbels, the wife of Nazi propaganda minister Joseph Goebbels and a prominent figure in Nazi Germany.
  • D. Johanna
    Johanna is a Hungarian experimental opera film reimagining the story of Joan of Arc in a modern hospital setting, directed by Kornél Mundruczó.
  • E. Joanna
    Joanna is a feminine given name used in various cultures, often associated with forms of the name John and shared by many notable historical and contemporary figures.
  • 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_69d6ad9cac2c81908e8a7bed82d1e21d completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d954a325948190994bcfc9d571a3a8 completed April 10, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f65eb8ec888190b46a0b48840efd20 completed May 2, 2026, 8:29 p.m.
Created at: April 8, 2026, 11:50 p.m.