Triple

T13714432
Position Surface form Disambiguated ID Type / Status
Subject Eugenia E328856 entity
Predicate hasVariant P455 FINISHED
Object Yevgenia E1065148 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: Yevgenia | Statement: [Eugenia, hasVariant, Yevgenia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Yevgenia
Context triple: [Eugenia, hasVariant, Yevgenia]
  • A. Evgenia chosen
    Evgenia is a feminine given name commonly used in Slavic and Greek cultures, derived from the Greek name Eugenia meaning "well-born" or "noble."
  • B. Yulia
    Yulia is a feminine given name, commonly used in Slavic countries as a form of the name Julia.
  • C. Irina
    Irina is a feminine given name commonly used in Slavic and other Eastern European cultures, derived from the Greek name Irene meaning "peace."
  • D. Svetlana
    Svetlana is a feminine given name of Slavic origin, most notably borne by Svetlana Alliluyeva, the daughter of Soviet leader Joseph Stalin.
  • E. Galina
    Galina is a feminine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd43973cf08190a417d0cca9dd314a completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7c6fcddf08190bee3dce22be39a34 completed May 3, 2026, 10:06 p.m.
Created at: April 9, 2026, 9:54 p.m.