Triple

T8184185
Position Surface form Disambiguated ID Type / Status
Subject Jeanne E191141 entity
Predicate equivalentName P6530 FINISHED
Object Ivana E258038 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: Ivana | Statement: [Jeanne, equivalentName, Ivana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ivana
Context triple: [Jeanne, equivalentName, Ivana]
  • A. Ivana
    Ivana is a small coastal municipality in the province of Batanes in the northern Philippines, known for its traditional stone houses and scenic seascapes.
  • B. Ivana chosen
    Ivana is a feminine given name, common in Slavic countries, that is a variant of the name Joanna/John.
  • C. 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.
  • D. Marija
    Marija is a feminine given name commonly used in Slavic and other European cultures, equivalent to "Maria" or "Mary."
  • E. Ivana Kobilca
    Ivana Kobilca was a prominent Slovenian realist painter of the late 19th and early 20th centuries, known for her portraits, genre scenes, and role in shaping Slovenian national art.
  • 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_69ca82c4538081909404325aa5639483 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4c4f4ef88190ad346edad14b67ee completed March 31, 2026, 4:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccbf95fd5c81908391dc160723b9e9 completed April 1, 2026, 6:47 a.m.
Created at: March 30, 2026, 5:41 p.m.