Triple

T12972333
Position Surface form Disambiguated ID Type / Status
Subject Peter Zinner E321430 entity
Predicate name P16 FINISHED
Object Peter Zinner E321430 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: Peter Zinner | Statement: [Peter Zinner, name, Peter Zinner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Peter Zinner
Context triple: [Peter Zinner, name, Peter Zinner]
  • A. Peter Zinner chosen
    Peter Zinner was an Austrian-born American film editor renowned for his work on major Hollywood films, including classics like The Deer Hunter and The Godfather.
  • B. Peter Zimroth
    Peter Zimroth was an American lawyer and legal scholar who served as New York City’s Corporation Counsel and later as the court-appointed monitor overseeing reforms to the NYPD’s stop-and-frisk practices.
  • C. Joachim Haspinger
    Joachim Haspinger was a Capuchin priest and military leader who became a prominent figure in the Tyrolean uprising against Napoleonic and Bavarian rule in 1809.
  • D. Thomas Häßler
    Thomas Häßler is a former German attacking midfielder renowned for his playmaking skills and key role in Germany’s 1990 World Cup and Euro 1996 triumphs.
  • E. Peter Riedler
    Peter Riedler is an Austrian academic and university administrator who serves as rector of the University of Graz.
  • 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_69fed314bb9481908144c5399aa62ffa completed May 9, 2026, 6:24 a.m.
Created at: April 9, 2026, 8:36 p.m.