Triple

T9836408
Position Surface form Disambiguated ID Type / Status
Subject Tamara Geva E239111 entity
Predicate countryOfCitizenship P2 FINISHED
Object Russia E10011 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: Russia | Statement: [Tamara Geva, countryOfCitizenship, Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russia
Context triple: [Tamara Geva, countryOfCitizenship, Russia]
  • 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. Rusko
    Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
  • D. Rusa
    Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
  • 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_69ca84e314108190978324a4bdb959f8 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb33b07688190b78a70cf535c3efc completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5a1a3b88190a1b4561a9a780e41 completed April 5, 2026, 3:23 a.m.
Created at: March 30, 2026, 8:33 p.m.