Triple

T14413972
Position Surface form Disambiguated ID Type / Status
Subject The Changeling E357400 entity
Predicate editedBy P1954 FINISHED
Object Lorenzo Marinelli
Lorenzo Marinelli is an editor known for his work on the film "The Changeling."
E1409450 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: Lorenzo Marinelli | Statement: [The Changeling, editedBy, Lorenzo Marinelli]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lorenzo Marinelli
Context triple: [The Changeling, editedBy, Lorenzo Marinelli]
  • A. Marcello Masciocchi
    Marcello Masciocchi was an Italian cinematographer known for his work on numerous mid-20th-century films.
  • B. Corrado Feroci
    Corrado Feroci was an Italian-born sculptor who became a leading figure in modern Thai art and is best known for his monumental public works in Bangkok.
  • C. Giorgio Arlorio
    Giorgio Arlorio was an Italian screenwriter known for his work on politically charged and genre films, including notable collaborations in 1960s and 1970s Italian cinema.
  • D. Giuseppe Bertolucci
    Giuseppe Bertolucci was an Italian film director and screenwriter known for his work in politically engaged and experimental cinema.
  • E. Marcello Nizzoli
    Marcello Nizzoli was an influential Italian industrial designer and graphic artist best known for shaping the modernist aesthetic of Olivetti’s typewriters and office machines in the mid-20th century.
  • 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: Lorenzo Marinelli
Triple: [The Changeling, editedBy, Lorenzo Marinelli]
Generated description
Lorenzo Marinelli is an editor known for his work on the film "The Changeling."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Lorenzo Marinelli
Target entity description: Lorenzo Marinelli is an editor known for his work on the film "The Changeling."
  • A. Marcello Masciocchi
    Marcello Masciocchi was an Italian cinematographer known for his work on numerous mid-20th-century films.
  • B. Corrado Feroci
    Corrado Feroci was an Italian-born sculptor who became a leading figure in modern Thai art and is best known for his monumental public works in Bangkok.
  • C. Giorgio Arlorio
    Giorgio Arlorio was an Italian screenwriter known for his work on politically charged and genre films, including notable collaborations in 1960s and 1970s Italian cinema.
  • D. Giuseppe Bertolucci
    Giuseppe Bertolucci was an Italian film director and screenwriter known for his work in politically engaged and experimental cinema.
  • E. Marcello Nizzoli
    Marcello Nizzoli was an influential Italian industrial designer and graphic artist best known for shaping the modernist aesthetic of Olivetti’s typewriters and office machines in the mid-20th century.
  • 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90cb3c708190822f5506ebf7ee9d completed April 14, 2026, 7:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0815e456ec8190986280b85fc017c7 completed May 16, 2026, 6:59 a.m.
NEDg Description generation batch_6a081a539a7c819089d8a308102e7d20 completed May 16, 2026, 7:18 a.m.
NED2 Entity disambiguation (via description) batch_6a081ab0e7208190b6020f9f9974084b completed May 16, 2026, 7:20 a.m.
Created at: April 10, 2026, 1:17 a.m.