Triple

T18533500
Position Surface form Disambiguated ID Type / Status
Subject Minx E452900 entity
Predicate executiveProducer P7225 FINISHED
Object Dan Magnante
Dan Magnante is a television producer best known for his executive production work on the series "Minx."
E1333558 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: Dan Magnante | Statement: [Minx, executiveProducer, Dan Magnante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dan Magnante
Context triple: [Minx, executiveProducer, Dan Magnante]
  • A. Anthony Marentino
    Anthony Marentino is a flamboyant, quick-witted wedding planner and stylist best known as Charlotte York’s close friend and eventual husband on the television series "Sex and the City."
  • B. Charles Nicoletti
    Charles Nicoletti was a Chicago mob hitman associated with the Chicago Outfit and reputed to be one of its most feared enforcers during the mid-20th century.
  • C. Michael Ferraro
    Michael Ferraro is a co-founder of Blue Sky Studios, the acclaimed animation company behind films such as the Ice Age series.
  • D. Dan Janvey
    Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
  • E. Dan Frank
    Dan Frank was an influential American book editor known for shaping contemporary literary fiction and nonfiction during his long tenure at major publishing houses.
  • 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: Dan Magnante
Triple: [Minx, executiveProducer, Dan Magnante]
Generated description
Dan Magnante is a television producer best known for his executive production work on the series "Minx."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Dan Magnante
Target entity description: Dan Magnante is a television producer best known for his executive production work on the series "Minx."
  • A. Anthony Marentino
    Anthony Marentino is a flamboyant, quick-witted wedding planner and stylist best known as Charlotte York’s close friend and eventual husband on the television series "Sex and the City."
  • B. Charles Nicoletti
    Charles Nicoletti was a Chicago mob hitman associated with the Chicago Outfit and reputed to be one of its most feared enforcers during the mid-20th century.
  • C. Michael Ferraro
    Michael Ferraro is a co-founder of Blue Sky Studios, the acclaimed animation company behind films such as the Ice Age series.
  • D. Dan Janvey
    Dan Janvey is an American film producer known for his work on acclaimed independent films, including the Academy Award–winning "Nomadland."
  • E. Dan Frank
    Dan Frank was an influential American book editor known for shaping contemporary literary fiction and nonfiction during his long tenure at major publishing houses.
  • 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_69d8d387b5548190aa030dad2cb4947e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e533ffc38881909f8ee132314f58a3 completed April 19, 2026, 7:58 p.m.
NED1 Entity disambiguation (via context triple) batch_6a050371a00081908cc8745885705b16 completed May 13, 2026, 11:04 p.m.
NEDg Description generation batch_6a05051c972c81909518b1cd85aa820b completed May 13, 2026, 11:11 p.m.
NED2 Entity disambiguation (via description) batch_6a05056d181881909b803a9c3efc58ba completed May 13, 2026, 11:12 p.m.
Created at: April 10, 2026, 11:37 a.m.