Triple

T15625628
Position Surface form Disambiguated ID Type / Status
Subject Dirty Grandpa E375668 entity
Predicate producer P490 FINISHED
Object Jason Barrett
Jason Barrett is a film producer known for his work on the comedy movie "Dirty Grandpa."
E1170597 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: Jason Barrett | Statement: [Dirty Grandpa, producer, Jason Barrett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jason Barrett
Context triple: [Dirty Grandpa, producer, Jason Barrett]
  • A. Matthew Barrett
    Matthew Barrett is an Irish cardiologist best known as the long-term partner of former Taoiseach and current Tánaiste Leo Varadkar.
  • B. Craig Barrett
    Craig Barrett is an American business executive and engineer best known for serving as CEO and chairman of Intel Corporation.
  • C. Larry Barrett
    Larry Barrett was one of the judges who scored the historic 1975 heavyweight boxing match between Muhammad Ali and Joe Frazier, known as the "Thrilla in Manila."
  • D. James Lee Barrett
    James Lee Barrett was an American screenwriter and producer known for his work on films such as "Shenandoah," "The Greatest Story Ever Told," and "Fools' Parade."
  • E. Michael Barrett
    Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
  • 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: Jason Barrett
Triple: [Dirty Grandpa, producer, Jason Barrett]
Generated description
Jason Barrett is a film producer known for his work on the comedy movie "Dirty Grandpa."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Jason Barrett
Target entity description: Jason Barrett is a film producer known for his work on the comedy movie "Dirty Grandpa."
  • A. Matthew Barrett
    Matthew Barrett is an Irish cardiologist best known as the long-term partner of former Taoiseach and current Tánaiste Leo Varadkar.
  • B. Craig Barrett
    Craig Barrett is an American business executive and engineer best known for serving as CEO and chairman of Intel Corporation.
  • C. Larry Barrett
    Larry Barrett was one of the judges who scored the historic 1975 heavyweight boxing match between Muhammad Ali and Joe Frazier, known as the "Thrilla in Manila."
  • D. James Lee Barrett
    James Lee Barrett was an American screenwriter and producer known for his work on films such as "Shenandoah," "The Greatest Story Ever Told," and "Fools' Parade."
  • E. Michael Barrett
    Michael Barrett is an American cinematographer known for his work on numerous feature films and television projects, including mainstream comedies and action movies.
  • 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_69d85cd035a48190b73d5579ab73969a completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e9e5e248190ae54cda1fde51efb completed April 16, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6ece07608190a705f108c8c2979a completed May 9, 2026, 5:28 p.m.
NEDg Description generation batch_69ff6fb61144819085460226d406161d completed May 9, 2026, 5:32 p.m.
NED2 Entity disambiguation (via description) batch_69ff705b1ea08190bf08b99c19715e57 completed May 9, 2026, 5:35 p.m.
Created at: April 10, 2026, 4:14 a.m.