Triple

T22633271
Position Surface form Disambiguated ID Type / Status
Subject Nathalie Péchalat E558609 entity
Predicate trainedInCountry P41472 FINISHED
Object 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: Russia | Statement: [Nathalie Péchalat, trainedInCountry, Russia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Russia
Context triple: [Nathalie Péchalat, trainedInCountry, 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. Rusko
    Rusko is a British electronic music producer and DJ known for pioneering the modern dubstep sound.
  • E. Rusa
    Rusa is a genus of deer native to South and Southeast Asia, including species such as the Javan rusa and sambar.
  • 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_69e245467d9881908d6985bd0db7a1f1 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1700ab4308190a16b0a1b2a0210fd completed April 29, 2026, 2:42 a.m.
Created at: April 17, 2026, 3:03 p.m.