Triple

T14353182
Position Surface form Disambiguated ID Type / Status
Subject Viktoria E355903 entity
Predicate hasSpellingVariant P457 FINISHED
Object Wiktoria E355903 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: Wiktoria | Statement: [Viktoria, hasSpellingVariant, Wiktoria]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wiktoria
Context triple: [Viktoria, hasSpellingVariant, Wiktoria]
  • A. Zofia
    Zofia is a feminine given name of Slavic origin, particularly common in Poland and other Central and Eastern European countries.
  • B. Violetta Helena Krakowska
    Violetta Helena Krakowska was a spouse of a member of the extended Einstein family, connected by marriage to the lineage of physicist Albert Einstein.
  • C. Józefina
    Józefina is the Polish form of the female given name Josephine, commonly used in Poland and among Polish-speaking communities.
  • D. Bronislava
    Bronislava is a feminine given name of Slavic origin, notably borne by the influential ballet dancer and choreographer Bronislava Nijinska.
  • E. Viktoria chosen
    Viktoria is a feminine given name of Latin origin, commonly used in various European countries as a variant of "Victoria."
  • 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_69d82790a7e08190877e2d349b2e8d8e completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8f4ff1e48190bd9419d70098cede completed April 14, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd4c44ff4c8190bbcc7a34b98ac330 completed May 8, 2026, 2:36 a.m.
Created at: April 10, 2026, 1:14 a.m.