Triple

T5461278
Position Surface form Disambiguated ID Type / Status
Subject Natalia Goncharova E122598 entity
Predicate givenName P17 FINISHED
Object Natalia E281523 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: Natalia | Statement: [Natalia Goncharova, givenName, Natalia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Natalia
Context triple: [Natalia Goncharova, givenName, Natalia]
  • A. Natalia
    Natalia was a short-lived Boer republic established in the 1830s in what is now KwaZulu-Natal, South Africa.
  • B. Natalya chosen
    Natalya is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Latin name Natalia.
  • C. Yelena
    Yelena is a feminine given name of Slavic origin, commonly used in Russian-speaking countries and equivalent to Helen or Helena in English.
  • D. Nina
    Nina is a feminine given name used in various cultures, often as a short form of names like Antonina or Giannina, and borne by numerous notable figures in the arts and public life.
  • E. Nina
    Nina is a Danish fashion model best known for her appearances in the Sports Illustrated Swimsuit Issue and various high-profile advertising campaigns.
  • 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_69bd4643f16081908d7f29e08096115a completed March 20, 2026, 1:06 p.m.
NER Named-entity recognition batch_69bd9201dbfc8190bea22d6ecbc25b3e completed March 20, 2026, 6:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf414c39a4819098f2862f3c4594c0 completed March 22, 2026, 1:09 a.m.
Created at: March 20, 2026, 2:08 p.m.