Triple

T8731277
Position Surface form Disambiguated ID Type / Status
Subject The Hunchback of Notre Dame (1956 film) E207259 entity
Predicate castMember P1668 FINISHED
Object André Versini
André Versini was a French actor and screenwriter known for his roles in mid-20th-century French cinema.
E761322 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: André Versini | Statement: [The Hunchback of Notre Dame (1956 film), castMember, André Versini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: André Versini
Context triple: [The Hunchback of Notre Dame (1956 film), castMember, André Versini]
  • A. Bernardo Fergioni
    Bernardo Fergioni was an Italian painter and teacher active in the 18th century, best known today as the early mentor of the renowned marine painter Joseph Vernet.
  • B. Rinaldo Melucci
    Rinaldo Melucci is an Italian politician best known for serving as the mayor of the city of Taranto.
  • C. Giulio Petroni
    Giulio Petroni was an Italian film director best known for his influential work in the Spaghetti Western genre during the 1960s and 1970s.
  • D. Guido Saracco
    Guido Saracco is an Italian chemical engineer and academic who serves as rector of the Polytechnic University of Turin.
  • E. Fabio Conversi
    Fabio Conversi is an Italian film producer best known for his work on acclaimed art-house and auteur-driven films, including the Oscar-winning "The Great Beauty."
  • 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: André Versini
Triple: [The Hunchback of Notre Dame (1956 film), castMember, André Versini]
Generated description
André Versini was a French actor and screenwriter known for his roles in mid-20th-century French cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: André Versini
Target entity description: André Versini was a French actor and screenwriter known for his roles in mid-20th-century French cinema.
  • A. Bernardo Fergioni
    Bernardo Fergioni was an Italian painter and teacher active in the 18th century, best known today as the early mentor of the renowned marine painter Joseph Vernet.
  • B. Rinaldo Melucci
    Rinaldo Melucci is an Italian politician best known for serving as the mayor of the city of Taranto.
  • C. Giulio Petroni
    Giulio Petroni was an Italian film director best known for his influential work in the Spaghetti Western genre during the 1960s and 1970s.
  • D. Guido Saracco
    Guido Saracco is an Italian chemical engineer and academic who serves as rector of the Polytechnic University of Turin.
  • E. Fabio Conversi
    Fabio Conversi is an Italian film producer best known for his work on acclaimed art-house and auteur-driven films, including the Oscar-winning "The Great Beauty."
  • 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_69ca8358e4008190898471a59b96c301 completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d27efb88190b42d5bc9774d9c63 completed March 31, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf88dc7ba88190865957c8d344fa00 completed April 3, 2026, 9:31 a.m.
NEDg Description generation batch_69cf8bb6d7dc8190a91864130513fa4e completed April 3, 2026, 9:43 a.m.
NED2 Entity disambiguation (via description) batch_69cf8ca3e2788190a33fb28132944759 completed April 3, 2026, 9:47 a.m.
Created at: March 30, 2026, 6:37 p.m.