Triple

T7288290
Position Surface form Disambiguated ID Type / Status
Subject In Too Deep E163929 entity
Predicate screenwriter P2831 FINISHED
Object Michael Henry Brown
Michael Henry Brown is a screenwriter best known for his work on the crime thriller film "In Too Deep."
 E664664 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: Michael Henry Brown | Statement: [In Too Deep, screenwriter, Michael Henry Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Michael Henry Brown
Context triple: [In Too Deep, screenwriter, Michael Henry Brown]
  • A. David Marvin Blake
    David Marvin Blake is an American rapper, DJ, and record producer best known by his stage name DJ Quik, a prominent figure in West Coast hip hop.
  • B. Jonathan Brown
    Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
  • C. David Brown
    David Brown was an American film producer best known for co-producing blockbuster hits such as "Jaws" and "The Sting."
  • D. David Brown
    David Brown was a British industrialist and owner of Aston Martin whose initials were used to designate the company’s iconic “DB” series of sports cars.
  • E. David Brown
    David Brown was an American bassist best known for his work with the Latin rock band Santana during their classic late-1960s and early-1970s period.
  • 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: Michael Henry Brown
Triple: [In Too Deep, screenwriter, Michael Henry Brown]
Generated description
Michael Henry Brown is a screenwriter best known for his work on the crime thriller film "In Too Deep."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Michael Henry Brown
Target entity description: Michael Henry Brown is a screenwriter best known for his work on the crime thriller film "In Too Deep."
  • A. David Marvin Blake
    David Marvin Blake is an American rapper, DJ, and record producer best known by his stage name DJ Quik, a prominent figure in West Coast hip hop.
  • B. Jonathan Brown
    Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
  • C. David Brown
    David Brown was an American film producer best known for co-producing blockbuster hits such as "Jaws" and "The Sting."
  • D. David Brown
    David Brown was a British industrialist and owner of Aston Martin whose initials were used to designate the company’s iconic “DB” series of sports cars.
  • E. David Brown
    David Brown was an American bassist best known for his work with the Latin rock band Santana during their classic late-1960s and early-1970s period.
  • 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_69c6886093b88190a254b1ce6db8bae7 completed March 27, 2026, 1:38 p.m.
NER Named-entity recognition batch_69c6eb6a73fc8190ae5ce81fd3e46d87 completed March 27, 2026, 8:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c827604a808190a362734e864123aa completed March 28, 2026, 7:09 p.m.
NEDg Description generation batch_69c828050b0481908723e61756aa2d68 completed March 28, 2026, 7:12 p.m.
NED2 Entity disambiguation (via description) batch_69c82900c41481909f886fc565c57420 completed March 28, 2026, 7:16 p.m.
Created at: March 27, 2026, 2:59 p.m.