Triple

T11666393
Position Surface form Disambiguated ID Type / Status
Subject Raf Vallone E277260 entity
Predicate spouse P13 FINISHED
Object Elena Varzi
Elena Varzi was an Italian film actress known for her roles in postwar Italian cinema, particularly in neorealist and melodramatic films.
E941513 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: Elena Varzi | Statement: [Raf Vallone, spouse, Elena Varzi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Elena Varzi
Context triple: [Raf Vallone, spouse, Elena Varzi]
  • A. Valentina Cervi
    Valentina Cervi is an Italian actress known for her work in European cinema and international productions, including both film and television roles.
  • B. Carla Voltolina
    Carla Voltolina was an Italian journalist, psychologist, and former partisan who was married to President Sandro Pertini and known for her social and humanitarian engagement.
  • C. Daniela Nardini
    Daniela Nardini is a Scottish actress best known for her BAFTA-winning role as Anna Forbes in the BBC drama series "This Life."
  • D. Valentina Moretti
    Valentina Moretti is an individual notable enough to be recognized as a prominent bearer of the Italian surname Moretti.
  • E. Liana Dognini
    Liana Dognini is a screenwriter best known for co-writing the film adaptation of the novel "Morvern Callar."
  • 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: Elena Varzi
Triple: [Raf Vallone, spouse, Elena Varzi]
Generated description
Elena Varzi was an Italian film actress known for her roles in postwar Italian cinema, particularly in neorealist and melodramatic films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Elena Varzi
Target entity description: Elena Varzi was an Italian film actress known for her roles in postwar Italian cinema, particularly in neorealist and melodramatic films.
  • A. Valentina Cervi
    Valentina Cervi is an Italian actress known for her work in European cinema and international productions, including both film and television roles.
  • B. Carla Voltolina
    Carla Voltolina was an Italian journalist, psychologist, and former partisan who was married to President Sandro Pertini and known for her social and humanitarian engagement.
  • C. Daniela Nardini
    Daniela Nardini is a Scottish actress best known for her BAFTA-winning role as Anna Forbes in the BBC drama series "This Life."
  • D. Valentina Moretti
    Valentina Moretti is an individual notable enough to be recognized as a prominent bearer of the Italian surname Moretti.
  • E. Liana Dognini
    Liana Dognini is a screenwriter best known for co-writing the film adaptation of the novel "Morvern Callar."
  • 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_69d6aafd0a448190b44da30af8c6c519 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a43f438081909da476294a057c38 completed April 10, 2026, 7:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef82e252fc819082b5c8a33fcf861a completed April 27, 2026, 3:38 p.m.
NEDg Description generation batch_69ef96ab29d48190b225504856007384 completed April 27, 2026, 5:02 p.m.
NED2 Entity disambiguation (via description) batch_69efd64bfa7081909715aa64d80fadf3 completed April 27, 2026, 9:34 p.m.
Created at: April 8, 2026, 9:39 p.m.