Triple

T11475649
Position Surface form Disambiguated ID Type / Status
Subject Don Giovanni E272018 entity
Predicate character P662 FINISHED
Object Donna Anna E468746 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: Donna Anna | Statement: [Don Giovanni, character, Donna Anna]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Donna Anna
Context triple: [Don Giovanni, character, Donna Anna]
  • A. Donna Anna chosen
    Donna Anna is a principal soprano role in Mozart’s opera "Don Giovanni," known for its dramatic intensity and vocal virtuosity.
  • B. Emilia Galotti
    Emilia Galotti is an 18th-century bourgeois tragedy by Gotthold Ephraim Lessing that critiques absolutist power and social hierarchy through the story of a virtuous young woman destroyed by a corrupt prince.
  • C. Caterina
    Caterina is an Italian given name, equivalent to Catherine, commonly used for women in Italian-speaking and related cultures.
  • D. Caterina Tezio
    Caterina Tezio was the wife of renowned Italian Baroque sculptor and architect Gian Lorenzo Bernini.
  • E. Lucrezia del Caccia
    Lucrezia del Caccia was a Florentine noblewoman of the late 15th century and the mother of Lisa Gherardini, the woman believed to be depicted in Leonardo da Vinci’s Mona Lisa.
  • 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_69d6aae0c8d881908a5a360c0be3242e completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8294c8dc48190a515f83c99405a3b completed April 9, 2026, 10:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5e965eebc8190822247b1abc13483 completed April 20, 2026, 8:52 a.m.
Created at: April 8, 2026, 9:36 p.m.