Triple

T20006950
Position Surface form Disambiguated ID Type / Status
Subject Zen E494483 entity
Predicate castMember P1668 FINISHED
Object Francesca Inaudi
Francesca Inaudi is an Italian actress known for her work in film, television, and theater.
E1410374 NE FINISHED

How this triple was built (4 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: Francesca Inaudi | Statement: [Zen, castMember, Francesca Inaudi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Francesca Inaudi
Context triple: [Zen, castMember, Francesca Inaudi]
  • A. Silvia Franceschini
    Silvia Franceschini is known primarily as the wife of Italian politician and former Minister of Culture Dario Franceschini.
  • B. Francesca De Scaffa
    Francesca De Scaffa was an actress best known for her marriage to American film actor Bruce Cabot.
  • C. Francesca Leone
    Francesca Leone is an Italian contemporary artist known for her large-scale mixed-media works that explore themes of urban decay, memory, and the human condition.
  • D. Francesca Vanini
    Francesca Vanini is a character in Jean-Luc Godard’s 1963 film "Le Mépris," appearing within its story of marital breakdown and the troubled production of a film adaptation of "The Odyssey."
  • E. Manuela Testolini
    Manuela Testolini is a Canadian businesswoman and philanthropist, known for founding the nonprofit In a Perfect World and for her previous marriage to musician Prince.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Francesca Inaudi
Triple: [Zen, castMember, Francesca Inaudi]
Generated description
Francesca Inaudi is an Italian actress known for her work in film, television, and theater.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Francesca Inaudi
Target entity description: Francesca Inaudi is an Italian actress known for her work in film, television, and theater.
  • A. Silvia Franceschini
    Silvia Franceschini is known primarily as the wife of Italian politician and former Minister of Culture Dario Franceschini.
  • B. Francesca De Scaffa
    Francesca De Scaffa was an actress best known for her marriage to American film actor Bruce Cabot.
  • C. Francesca Leone
    Francesca Leone is an Italian contemporary artist known for her large-scale mixed-media works that explore themes of urban decay, memory, and the human condition.
  • D. Francesca Vanini
    Francesca Vanini is a character in Jean-Luc Godard’s 1963 film "Le Mépris," appearing within its story of marital breakdown and the troubled production of a film adaptation of "The Odyssey."
  • E. Manuela Testolini
    Manuela Testolini is a Canadian businesswoman and philanthropist, known for founding the nonprofit In a Perfect World and for her previous marriage to musician Prince.
  • F. None of above. chosen

Provenance (5 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_69da626b2d748190886981ea90c8b2ea completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e661a648a88190853ee741edcf6ca2 completed April 20, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_6a081f296c208190bca5ec44af8db78c completed May 16, 2026, 7:39 a.m.
NEDg Description generation batch_6a081fcc025081909292799ee8abd779 completed May 16, 2026, 7:42 a.m.
NED2 Entity disambiguation (via description) batch_6a08208c203c819083abea34d10d5e4e completed May 16, 2026, 7:45 a.m.
Created at: April 11, 2026, 3:33 p.m.