Triple

T17344392
Position Surface form Disambiguated ID Type / Status
Subject Vasily Petrenko E421644 entity
Predicate name P16 FINISHED
Object Vasily Petrenko E421644 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: Vasily Petrenko | Statement: [Vasily Petrenko, name, Vasily Petrenko]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vasily Petrenko
Context triple: [Vasily Petrenko, name, Vasily Petrenko]
  • A. Vasily Petrenko chosen
    Vasily Petrenko is a Russian conductor renowned for his dynamic interpretations and leadership of major orchestras in Europe and beyond.
  • B. Igor Petrenko
    Igor Petrenko is a Russian film and television actor known for leading roles in historical and crime dramas.
  • C. Vladimir Jurowski
    Vladimir Jurowski is a renowned Russian-born conductor acclaimed for his interpretations of opera and symphonic repertoire and leadership of major European orchestras and opera houses.
  • D. Viktor Petrenko
    Viktor Petrenko is a Ukrainian figure skater best known for winning the men's singles gold medal at the 1992 Winter Olympics.
  • E. Valery Gergiev
    Valery Gergiev is a prominent Russian conductor renowned for his long tenure leading the Mariinsky Theatre and for his influential presence on the international classical music scene.
  • 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_69d889d520008190a26917a95bf1c2ea completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e43a27a350819086faf12e6bf9f0e2 completed April 19, 2026, 2:12 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c5be49c8190b27a4fe1df8e8ab6 completed May 11, 2026, 7:59 a.m.
Created at: April 10, 2026, 5:44 a.m.