Triple

T11683735
Position Surface form Disambiguated ID Type / Status
Subject Yolanda of Savoy E277684 entity
Predicate givenName P17 FINISHED
Object Margherita E100329 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: Margherita | Statement: [Yolanda of Savoy, givenName, Margherita]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Margherita
Context triple: [Yolanda of Savoy, givenName, Margherita]
  • A. Margherita chosen
    Margherita is the Italian form of the female given name Margaret, commonly used in Italy and other Italian-speaking communities.
  • B. Margherita
    Margherita is a coal-mining town in Assam, India, known for its tea gardens and proximity to the Patkai hills near the India–Myanmar border.
  • C. pizza Margherita
    Pizza Margherita is a classic Italian pizza topped with tomatoes, mozzarella, fresh basil, and olive oil, symbolizing the colors of the Italian flag.
  • D. Caprese
    Caprese is a small Tuscan village in Italy best known as the birthplace of the Renaissance artist Michelangelo.
  • E. Margherita Buy
    Margherita Buy is an acclaimed Italian actress known for her nuanced performances in contemporary Italian cinema and frequent collaborations with prominent directors.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a463f6448190a4c8e1651a2bd905 completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef142269d08190a9e5cf8d6268168b completed April 27, 2026, 7:45 a.m.
Created at: April 8, 2026, 9:40 p.m.