Triple

T12324598
Position Surface form Disambiguated ID Type / Status
Subject Evgeny Yasin E293794 entity
Predicate citizenship P2 FINISHED
Object USSR E363 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: USSR | Statement: [Evgeny Yasin, citizenship, USSR]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: USSR
Context triple: [Evgeny Yasin, citizenship, USSR]
  • A. Soviet Union chosen
    The Soviet Union was a socialist superpower that dominated Eastern Europe and led the communist bloc during the Cold War.
  • B. АН СССР
    АН СССР was the highest scientific institution of the Soviet Union, overseeing and coordinating research across a wide range of scientific disciplines.
  • C. Russian SFSR
    The Russian SFSR was the largest and most influential republic of the former Soviet Union, encompassing much of its political, economic, and cultural center.
  • D. Правительство СССР
    Правительство СССР было высшим исполнительным и распорядительным органом государственной власти Советского Союза, руководившим всей системой народных комиссариатов и министерств, экономикой и внутренней и внешней политикой страны.
  • E. Rusguniae
    Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
  • 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_69d6ab6ae0dc8190b1522a9c1c55c114 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93f4e7e588190b37e2413bc649198 completed April 10, 2026, 6:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f67c62e40481908a688912055c697c completed May 2, 2026, 10:36 p.m.
Created at: April 8, 2026, 9:53 p.m.