Triple

T3777899
Position Surface form Disambiguated ID Type / Status
Subject Viktor Petrenko E83351 entity
Predicate givenName P17 FINISHED
Object Viktor E75938 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: Viktor | Statement: [Viktor Petrenko, givenName, Viktor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viktor
Context triple: [Viktor Petrenko, givenName, Viktor]
  • A. Viktor chosen
    Viktor is the given name of Viktor Frankl, the Austrian neurologist, psychiatrist, and Holocaust survivor who founded logotherapy and wrote "Man’s Search for Meaning."
  • B. Viktor
    Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
  • C. Eduard
    Eduard is a central character in Paulo Coelho’s novel "Veronika Decides to Die," portrayed as a sensitive, introspective young man whose relationship with the protagonist profoundly influences her view of life and death.
  • D. Eduard
    Eduard was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
  • E. Vasily
    Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc5d3dbc8190b6ab118a56acd5a3 completed March 8, 2026, 7:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69be5c69987881908dc2b6286fec73c2 completed March 21, 2026, 8:52 a.m.
Created at: March 8, 2026, 3:36 p.m.