Triple

T9790015
Position Surface form Disambiguated ID Type / Status
Subject The Nut Job E237582 entity
Predicate editingBy P1954 FINISHED
Object Paul Hunter
Paul Hunter is a film editor known for his work on animated feature films such as "The Nut Job."
 E821588 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: Paul Hunter | Statement: [The Nut Job, editingBy, Paul Hunter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Paul Hunter
Context triple: [The Nut Job, editingBy, Paul Hunter]
  • A. Paul Hunter
    Paul Hunter is an acclaimed American music video director known for his visually innovative work with major artists across hip-hop, R&B, and pop.
  • B. John Higgins
    John Higgins is a British comic book artist and colorist best known for his influential work on landmark graphic novels such as Watchmen.
  • C. Paul Groth
    Paul Groth is a computer scientist known for his work in knowledge representation, semantic web technologies, and data provenance.
  • D. Peter Hewitt
    Peter Hewitt is a British film director known for helming family-oriented and fantasy comedies such as "Bill & Ted's Bogus Journey" and "Garfield: The Movie."
  • E. John C. Higgins
    John C. Higgins was an American screenwriter known for his work on mid-20th-century films, particularly in the crime and thriller genres.
  • 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: Paul Hunter
Triple: [The Nut Job, editingBy, Paul Hunter]
Generated description
Paul Hunter is a film editor known for his work on animated feature films such as "The Nut Job."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Paul Hunter
Target entity description: Paul Hunter is a film editor known for his work on animated feature films such as "The Nut Job."
  • A. Paul Hunter
    Paul Hunter is an acclaimed American music video director known for his visually innovative work with major artists across hip-hop, R&B, and pop.
  • B. John Higgins
    John Higgins is a British comic book artist and colorist best known for his influential work on landmark graphic novels such as Watchmen.
  • C. Paul Groth
    Paul Groth is a computer scientist known for his work in knowledge representation, semantic web technologies, and data provenance.
  • D. Peter Hewitt
    Peter Hewitt is a British film director known for helming family-oriented and fantasy comedies such as "Bill & Ted's Bogus Journey" and "Garfield: The Movie."
  • E. John C. Higgins
    John C. Higgins was an American screenwriter known for his work on mid-20th-century films, particularly in the crime and thriller genres.
  • 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_69ca84dc04488190b9c91193976c0960 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cda214875481909f39e1d4dbac1fdb completed April 1, 2026, 10:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1c42c9fe081908145911cad6723c2 completed April 5, 2026, 2:08 a.m.
NEDg Description generation batch_69d1c4eb7a0481908bbd72f6d28d4746 completed April 5, 2026, 2:11 a.m.
NED2 Entity disambiguation (via description) batch_69d1c5c0e6e88190bbf6eb379e6d1aa3 completed April 5, 2026, 2:15 a.m.
Created at: March 30, 2026, 8:28 p.m.