Triple

T8703185
Position Surface form Disambiguated ID Type / Status
Subject Viktor Jansson E206582 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 Jansson, givenName, Viktor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Viktor
Context triple: [Viktor Jansson, 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 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. Eduard
    Eduard is one of the central protagonists in Johann Wolfgang von Goethe’s novel "Elective Affinities," whose actions and relationships drive the story’s exploration of passion, marriage, and moral conflict.
  • 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_69ca835645e881908f00e3c8b51da81d completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc58b5b44081909e7b33c70fac236d completed March 31, 2026, 11:28 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1b953448190bac2c222fcc722bb completed April 3, 2026, 1:33 p.m.
Created at: March 30, 2026, 6:34 p.m.