Triple

T14694337
Position Surface form Disambiguated ID Type / Status
Subject Viktor Harder E345113 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 Harder, givenName, Viktor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viktor
Context triple: [Viktor Harder, 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 the given name of Eduard Bernstein, a prominent German social democratic theorist and politician associated with revisionist Marxism.
  • D. Eduard
    Eduard is the given name of Eduard Tisse, a prominent Soviet cinematographer best known for his collaborations with director Sergei Eisenstein.
  • E. Eduard
    Eduard is the given name of Eduard Zeller, a notable 19th-century German philosopher and historian of philosophy.
  • 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_69d822e34b348190ada4d1cdb6c7c226 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deb586e7108190be644db9cf9a4d99 completed April 14, 2026, 9:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe38857068819085e0d62829302abd completed May 8, 2026, 7:24 p.m.
Created at: April 10, 2026, 1:28 a.m.