Triple

T3587183
Position Surface form Disambiguated ID Type / Status
Subject Viktor Frankl E75938 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 Frankl, givenName, Viktor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viktor
Context triple: [Viktor Frankl, 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 was the younger son of physicist Albert Einstein, known for his promising studies in psychiatry and his lifelong struggle with schizophrenia.
  • D. 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.
  • 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_69ad85d6dc3c8190b491b79b83e25461 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc13a11608190a23d76efc1b50e3c completed March 8, 2026, 6:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4f01c47d881908e9489db7bf47b11 completed March 14, 2026, 5:20 a.m.
Created at: March 8, 2026, 3:22 p.m.