Triple

T12972369
Position Surface form Disambiguated ID Type / Status
Subject Peter Zinner E321430 entity
Predicate hasChild P369 FINISHED
Object Barbara Zinner E1074446 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: Barbara Zinner | Statement: [Peter Zinner, hasChild, Barbara Zinner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barbara Zinner
Context triple: [Peter Zinner, hasChild, Barbara Zinner]
  • A. Ruth Zinner chosen
    Ruth Zinner is known as the wife of Austrian-born American film editor Peter Zinner, who worked on acclaimed films such as "The Godfather" and "The Deer Hunter."
  • B. Barbara Blomberg
    Barbara Blomberg was a 16th-century German woman best known as the mistress of Holy Roman Emperor Charles V and the mother of his illegitimate son, John of Austria (the Elder).
  • C. Barbara Zoellner
    Barbara Zoellner is best known as the second wife of pioneering South African heart transplant surgeon Christiaan Barnard.
  • D. Barbara Fuchs
    Barbara Fuchs is a literary scholar known for her work on early modern Spanish and English literature, translation, and cultural exchange.
  • E. June Preisser
    June Preisser was an American film actress and dancer best known for her energetic supporting roles in 1930s and 1940s Hollywood musicals, often playing peppy, acrobatic teenagers.
  • 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_69d80763bd6c819094437da5b20b01d2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97e418d548190be1c73db76cb3aa8 completed April 10, 2026, 10:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc30fba90819096ea71152ed725e1 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 8:36 p.m.