Triple

T21415006
Position Surface form Disambiguated ID Type / Status
Subject Anton Lavrentyevich Gaganov E528276 entity
Predicate givenName P17 FINISHED
Object Anton NE NERFINISHED

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: Anton | Statement: [Anton Lavrentyevich Gaganov, givenName, Anton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anton
Context triple: [Anton Lavrentyevich Gaganov, givenName, Anton]
  • A. Anton chosen
    Anton is a masculine given name of Latin origin, commonly used in various European and Slavic countries.
  • B. Anton
    Anton is a film and television production company known for producing genre-driven and elevated horror projects.
  • C. Andrei
    Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
  • D. Anatole
    Anatole is the famously temperamental and gifted French chef employed by Aunt Dahlia in P. G. Wodehouse’s Jeeves and Wooster stories.
  • E. Anatole
    Anatole is a charming but morally dubious Russian aristocrat from Leo Tolstoy’s novel "War and Peace."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c454c248819093425d1099101c09 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ee62d16bfc8190a1c08dd9d0c80e02 completed April 26, 2026, 7:09 p.m.
Created at: April 16, 2026, 5:45 p.m.