Triple

T12016107
Position Surface form Disambiguated ID Type / Status
Subject Marchetti E286029 entity
Predicate hasNotableBearer P458 FINISHED
Object Gianni Marchetti
Gianni Marchetti was an Italian composer best known for his film scores, particularly in the 1960s and 1970s.
E976115 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: Gianni Marchetti | Statement: [Marchetti, hasNotableBearer, Gianni Marchetti]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gianni Marchetti
Context triple: [Marchetti, hasNotableBearer, Gianni Marchetti]
  • A. Maurizio Lombardi
    Maurizio Lombardi is an Italian actor known for his work in film and television, particularly in acclaimed European productions.
  • B. Gianfranco Franchini
    Gianfranco Franchini was an Italian architect best known as one of the co-designers of Paris’s iconic Centre Pompidou.
  • C. Gianpiero Marchetti
    Gianpiero Marchetti is an Italian former professional footballer known for playing as a defender in Serie A during the late 1960s and 1970s.
  • D. Maurizio Marchetti
    Maurizio Marchetti is an Italian politician known for his roles in regional and national political institutions.
  • E. Enrico Nicola Mancini
    Enrico Nicola Mancini, better known as Henry Mancini, was an American composer, conductor, and arranger renowned for his iconic film and television scores such as "The Pink Panther" and "Moon River."
  • 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: Gianni Marchetti
Triple: [Marchetti, hasNotableBearer, Gianni Marchetti]
Generated description
Gianni Marchetti was an Italian composer best known for his film scores, particularly in the 1960s and 1970s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gianni Marchetti
Target entity description: Gianni Marchetti was an Italian composer best known for his film scores, particularly in the 1960s and 1970s.
  • A. Maurizio Lombardi
    Maurizio Lombardi is an Italian actor known for his work in film and television, particularly in acclaimed European productions.
  • B. Gianfranco Franchini
    Gianfranco Franchini was an Italian architect best known as one of the co-designers of Paris’s iconic Centre Pompidou.
  • C. Gianpiero Marchetti
    Gianpiero Marchetti is an Italian former professional footballer known for playing as a defender in Serie A during the late 1960s and 1970s.
  • D. Maurizio Marchetti
    Maurizio Marchetti is an Italian politician known for his roles in regional and national political institutions.
  • E. Enrico Nicola Mancini
    Enrico Nicola Mancini, better known as Henry Mancini, was an American composer, conductor, and arranger renowned for his iconic film and television scores such as "The Pink Panther" and "Moon River."
  • 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_69d6ab45a368819084fce08bf0dc3705 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d903d9b17881908894be80d7c1b64e completed April 10, 2026, 2:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69f61e3af3cc8190b2a0e3531713aca5 completed May 2, 2026, 3:54 p.m.
NEDg Description generation batch_69f620759f348190baa9af5b33d4e37f completed May 2, 2026, 4:04 p.m.
NED2 Entity disambiguation (via description) batch_69f624bf23948190b182e4c31564d210 completed May 2, 2026, 4:22 p.m.
Created at: April 8, 2026, 9:47 p.m.