Triple

T23059313
Position Surface form Disambiguated ID Type / Status
Subject Count Vincenzo Torlato-Favrini E574251 entity
Predicate hasGivenName P17 FINISHED
Object Vincenzo 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: Vincenzo | Statement: [Count Vincenzo Torlato-Favrini, hasGivenName, Vincenzo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Vincenzo
Context triple: [Count Vincenzo Torlato-Favrini, hasGivenName, Vincenzo]
  • A. Vincenzo chosen
    Vincenzo is the Italian given name equivalent to Vincent, commonly used in Italy and among Italian-speaking communities.
  • B. Vittorio
    Vittorio is an Italian given name commonly used for men, derived from the Latin "Victor" meaning "winner" or "conqueror."
  • C. Gianfrancesco
    Gianfrancesco was an Italian nobleman of the Gonzaga family who became the first Marquis of Mantua in the early 15th century.
  • D. Gaetano
    Gaetano is an Italian given name, historically notable as the birth name of Saint Cajetan, a prominent 16th-century Catholic priest and reformer.
  • E. Ignazio
    Ignazio is an Italian given name, cognate to Ignacy and typically associated with the Latin-rooted names Ignatius and Ignacio.
  • 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_69e245ba7ae48190be606dbc54120e39 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1899e6c788190a2a862122cae8dc3 completed April 29, 2026, 4:31 a.m.
Created at: April 17, 2026, 3:55 p.m.