Triple

T12066582
Position Surface form Disambiguated ID Type / Status
Subject Juana E287311 entity
Predicate cognateOf P8954 FINISHED
Object Johanna E695409 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: [Juana, cognateOf, Johanna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Johanna
Context triple: [Juana, cognateOf, Johanna]
  • A. Johanna
    "Johanna" is a recurring, lyrically poignant love song from Stephen Sondheim's musical *Sweeney Todd: The Demon Barber of Fleet Street*.
  • B. Johanna
    Johanna is the birth name of Magda Goebbels, the wife of Nazi propaganda minister Joseph Goebbels and a prominent figure in Nazi Germany.
  • C. Johanna
    Johanna is the given name of Johanna Spyri, the Swiss author best known for creating the classic children's novel "Heidi."
  • 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 chosen
    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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d904423dc08190a47194422255c62e completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f658bb38819097547d392fcc5405 completed May 2, 2026, 1:04 p.m.
Created at: April 8, 2026, 9:48 p.m.