Triple

T16867214
Position Surface form Disambiguated ID Type / Status
Subject Curzon Line E410072 entity
Predicate separates P1175 FINISHED
Object Soviet Russia 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: Soviet Russia | Statement: [Curzon Line, separates, Soviet Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Soviet Russia
Context triple: [Curzon Line, separates, Soviet Russia]
  • 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. 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
    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 (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_69d88395e6c88190b22730f335107c14 completed April 10, 2026, 4:59 a.m.
NER Named-entity recognition batch_69e3b50983148190a116f7e7017ccb1c completed April 18, 2026, 4:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dbfd6898819083871544c119557c completed May 10, 2026, 7:26 p.m.
Created at: April 10, 2026, 5:24 a.m.