Triple

T22993193
Position Surface form Disambiguated ID Type / Status
Subject Mykola Fedoruk E572110 entity
Predicate givenName P17 FINISHED
Object Mykola 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: Mykola | Statement: [Mykola Fedoruk, givenName, Mykola]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mykola
Context triple: [Mykola Fedoruk, givenName, Mykola]
  • A. Mykola chosen
    Mykola is the Ukrainian form of the given name Nicholas, commonly used in Ukraine and among Ukrainian communities.
  • B. Mykhailo
    Mykhailo is a masculine given name of Slavic origin, commonly used in Ukrainian and other Eastern European cultures as a form of Michael.
  • C. Ihor
    Ihor is a Ukrainian given name, commonly considered the Ukrainian form of Igor.
  • D. Oleksy
    Oleksy is a Polish surname most notably borne by Józef Oleksy, a prominent Polish politician and former Prime Minister.
  • E. Yevhen
    Yevhen is a masculine given name of Slavic origin, commonly used in Ukraine and other Eastern European countries.
  • 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_69e245b535808190adef8a9df3c584db completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f182f017a88190b02d0649a3af5d99 completed April 29, 2026, 4:02 a.m.
Created at: April 17, 2026, 3:50 p.m.