Triple

T18279148
Position Surface form Disambiguated ID Type / Status
Subject Zlata Lilina E437817 entity
Predicate residence P75 FINISHED
Object Soviet Russia 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: Soviet Russia | Statement: [Zlata Lilina, residence, Soviet Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soviet Russia
Context triple: [Zlata Lilina, residence, Soviet Russia]
  • A. Soviet Union
    The Soviet Union was a socialist superpower that dominated Eastern Europe and led the communist bloc during the Cold War.
  • B. Rusguniae
    Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
  • C. АН СССР
    АН СССР was the highest scientific institution of the Soviet Union, overseeing and coordinating research across a wide range of scientific disciplines.
  • D. Russian SFSR chosen
    The Russian SFSR was the largest and most influential republic of the former Soviet Union, encompassing much of its political, economic, and cultural center.
  • E. Rusko
    Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
  • 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_69d8b914530c8190b4474d862a2b2a1b completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50054d1dc8190b31d02f617256e9d completed April 19, 2026, 4:18 p.m.
Created at: April 10, 2026, 10:34 a.m.