Triple

T17817470
Position Surface form Disambiguated ID Type / Status
Subject Camillo Filippo Ludovico Borghese E444884 entity
Predicate givenName P17 FINISHED
Object Filippo 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: Filippo | Statement: [Camillo Filippo Ludovico Borghese, givenName, Filippo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Filippo
Context triple: [Camillo Filippo Ludovico Borghese, givenName, Filippo]
  • A. Filippo chosen
    Filippo is an Italian given name most famously borne by former professional footballer and manager Filippo Inzaghi.
  • B. Francesco
    Francesco is a masculine given name of Italian origin, derived from the Latin Franciscus and commonly associated with figures such as Saint Francis of Assisi.
  • C. Francesco
    Francesco is the Italian given name of Frank Nitti, a notorious American mobster and key figure in Al Capone’s Chicago Outfit.
  • D. Francesco
    Francesco is the given name of Italian actor Franco Nero, renowned for his iconic role in the Spaghetti Western film "Django."
  • E. Francesco
    Francesco is the birth name of Frank Capra, the renowned Italian-American film director known for classic Hollywood movies such as "It's a Wonderful Life."
  • 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_69d8b9f0de78819099395b14db75a8a6 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48880457c81908214741d6cd7a1ee completed April 19, 2026, 7:47 a.m.
Created at: April 10, 2026, 10:14 a.m.