Triple

T21092484
Position Surface form Disambiguated ID Type / Status
Subject Ufa Federal Research Center of the Russian Academy of Sciences E519669 entity
Predicate geographicFocus P82 FINISHED
Object Russian Federation 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: Russian Federation | Statement: [Ufa Federal Research Center of the Russian Academy of Sciences, geographicFocus, Russian Federation]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russian Federation
Context triple: [Ufa Federal Research Center of the Russian Academy of Sciences, geographicFocus, Russian Federation]
  • A. Russia chosen
    Russia is the world’s largest country by land area, spanning Eastern Europe and northern Asia and exerting major political, military, and cultural influence globally.
  • B. ROSSIYA
    ROSSIYA is the radio callsign used by Rossiya Airlines, a major Russian carrier based in Saint Petersburg.
  • C. Rusa
    Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
  • D. Rusguniae
    Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
  • 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_69e0b507dd9081908fb8bfcbef4c8b46 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7094f6ebc8190a90b014755a9d4a6 completed April 21, 2026, 5:21 a.m.
Created at: April 16, 2026, 2:51 p.m.