Triple

T1324945
Position Surface form Disambiguated ID Type / Status
Subject Spartak Moscow E28304 entity
Predicate owner P347 FINISHED
Object Leonid Fedun E296728 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: Leonid Fedun | Statement: [Spartak Moscow, owner, Leonid Fedun]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonid Fedun
Context triple: [Spartak Moscow, owner, Leonid Fedun]
  • A. Leonid Fedun chosen
    Leonid Fedun is a Russian billionaire businessman and oil executive best known as the longtime owner and chairman of the football club Spartak Moscow.
  • B. Andrei Voronkov
    Andrei Voronkov is a computer scientist known for his influential work in automated reasoning and theorem proving.
  • C. Oleg Baklanov
    Oleg Baklanov was a Soviet politician and high-ranking official who played a key role as one of the hardline plotters in the failed 1991 coup attempt against Mikhail Gorbachev.
  • D. Andrei Zelentsov
    Andrei Zelentsov was a Soviet military commander best known for leading Red Army forces during the Winter War against Finland, including in the Battle of Suomussalmi.
  • E. Yuri Shchekochikhin
    Yuri Shchekochikhin was a prominent Russian investigative journalist, writer, and politician known for his hard-hitting reporting on corruption and organized crime, particularly through his work at Novaya Gazeta.
  • 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_69a498540a2481909e807a762280d3ba completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c19e81c0819092f85201ae34422a completed March 1, 2026, 10:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69afc61b715c81908bb4849b03617d85 completed March 10, 2026, 7:19 a.m.
Created at: March 1, 2026, 7:55 p.m.