Triple

T23319983
Position Surface form Disambiguated ID Type / Status
Subject Uyugan E591123 entity
Predicate locatedNear P294 FINISHED
Object Ivana 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: Ivana | Statement: [Uyugan, locatedNear, Ivana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivana
Context triple: [Uyugan, locatedNear, Ivana]
  • A. Ivana
    Ivana is a feminine given name, common in Slavic countries, that is a variant of the name Joanna/John.
  • B. Ivana chosen
    Ivana is a small coastal municipality in the province of Batanes in the northern Philippines, known for its traditional stone houses and scenic seascapes.
  • C. Ivana Omazic
    Ivana Omazic is a Croatian fashion designer best known for her tenure as creative director at the French luxury brand Céline in the mid-2000s.
  • D. Ivana Vrdoljak
    Ivana Vrdoljak is a Croatian sculptor and artist best known as the wife of actor Goran Višnjić.
  • E. Ivana Marie Zelníčková
    Ivana Marie Zelníčková, better known as Ivana Trump, was a Czech-American businesswoman, former model, and the first wife of Donald Trump, noted for her role in his early real estate empire and her own fashion and lifestyle ventures.
  • 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_69e25d1effe4819096907f95f610dbff completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1978440888190b316664812105d60 completed April 29, 2026, 5:30 a.m.
Created at: April 17, 2026, 5:07 p.m.