Triple

T2651504
Position Surface form Disambiguated ID Type / Status
Subject Johnny English Reborn E53908 entity
Predicate editedBy P1954 FINISHED
Object Guy Bensley
Guy Bensley is a film editor best known for his work on the comedy spy film "Johnny English Reborn."
E304842 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: Guy Bensley | Statement: [Johnny English Reborn, editedBy, Guy Bensley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Guy Bensley
Context triple: [Johnny English Reborn, editedBy, Guy Bensley]
  • A. Christopher Benstead
    Christopher Benstead is a British composer and music editor known for his film scores and sound work on major movies, including collaborations with director Guy Ritchie.
  • B. Andrew Bennison
    Andrew Bennison was an American screenwriter active during the early sound era of Hollywood cinema.
  • C. Sam Baldwin
    Sam Baldwin is the widowed architect and devoted father portrayed by Tom Hanks in the romantic comedy film "Sleepless in Seattle."
  • D. Stephen Burbank
    Stephen Burbank is a prominent legal scholar and professor known for his expertise in civil procedure and complex litigation at the University of Pennsylvania Law School.
  • E. Eric Bates
    Eric Bates is the young, wealthy boy in the 1982 comedy film "The Toy" who whimsically "purchases" a man as his personal companion, driving much of the movie’s plot and humor.
  • 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: Guy Bensley
Triple: [Johnny English Reborn, editedBy, Guy Bensley]
Generated description
Guy Bensley is a film editor best known for his work on the comedy spy film "Johnny English Reborn."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Guy Bensley
Target entity description: Guy Bensley is a film editor best known for his work on the comedy spy film "Johnny English Reborn."
  • A. Christopher Benstead
    Christopher Benstead is a British composer and music editor known for his film scores and sound work on major movies, including collaborations with director Guy Ritchie.
  • B. Andrew Bennison
    Andrew Bennison was an American screenwriter active during the early sound era of Hollywood cinema.
  • C. Sam Baldwin
    Sam Baldwin is the widowed architect and devoted father portrayed by Tom Hanks in the romantic comedy film "Sleepless in Seattle."
  • D. Stephen Burbank
    Stephen Burbank is a prominent legal scholar and professor known for his expertise in civil procedure and complex litigation at the University of Pennsylvania Law School.
  • E. Eric Bates
    Eric Bates is the young, wealthy boy in the 1982 comedy film "The Toy" who whimsically "purchases" a man as his personal companion, driving much of the movie’s plot and humor.
  • 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_69ab495e192081909c77b622e8e7e15a completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abd93071248190820197936e3167f7 completed March 7, 2026, 7:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d3d6a54819090068ef1807ca921 completed March 10, 2026, 1:31 p.m.
NEDg Description generation batch_69b01f73ff708190924f6e12d5688cc7 completed March 10, 2026, 1:41 p.m.
NED2 Entity disambiguation (via description) batch_69b020fe69b881909b576a5321126a7c completed March 10, 2026, 1:47 p.m.
Created at: March 6, 2026, 9:53 p.m.