Triple

T9830230
Position Surface form Disambiguated ID Type / Status
Subject Detroit (2017 film) E238763 entity
Predicate producer P490 FINISHED
Object Matthew Budman
Matthew Budman is a film producer known for his work on projects such as the crime drama "Detroit" (2017).
E871481 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: Matthew Budman | Statement: [Detroit (2017 film), producer, Matthew Budman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Matthew Budman
Context triple: [Detroit (2017 film), producer, Matthew Budman]
  • A. Morton Heiligman
    Morton Heiligman is an academic known for supervising the doctoral work of computer scientist and Smalltalk pioneer Adele Goldberg.
  • B. Arthur Grossman
    Arthur Grossman is the birth name of Arthur Freed, the influential American film producer and lyricist best known for his work on classic MGM musicals.
  • C. Pandro S. Berman
    Pandro S. Berman was a prominent American film producer of Hollywood’s classic era, known for overseeing numerous successful MGM and RKO pictures.
  • D. Tom Mendelsohn
    Tom Mendelsohn is an Australian man known primarily as the brother of acclaimed actor Ben Mendelsohn.
  • E. Steven Fierberg
    Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
  • 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: Matthew Budman
Triple: [Detroit (2017 film), producer, Matthew Budman]
Generated description
Matthew Budman is a film producer known for his work on projects such as the crime drama "Detroit" (2017).
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Matthew Budman
Target entity description: Matthew Budman is a film producer known for his work on projects such as the crime drama "Detroit" (2017).
  • A. Morton Heiligman
    Morton Heiligman is an academic known for supervising the doctoral work of computer scientist and Smalltalk pioneer Adele Goldberg.
  • B. Arthur Grossman
    Arthur Grossman is the birth name of Arthur Freed, the influential American film producer and lyricist best known for his work on classic MGM musicals.
  • C. Pandro S. Berman
    Pandro S. Berman was a prominent American film producer of Hollywood’s classic era, known for overseeing numerous successful MGM and RKO pictures.
  • D. Tom Mendelsohn
    Tom Mendelsohn is an Australian man known primarily as the brother of acclaimed actor Ben Mendelsohn.
  • E. Steven Fierberg
    Steven Fierberg is an American cinematographer known for his work on feature films and television series, including the romantic drama "Love & Other Drugs."
  • 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_69ca84e0dd1881909800765d1e21f735 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb3282a2481908913addf2b3fa58b completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9333d2e708190b0c8ec679bcb6ade completed April 10, 2026, 5:28 p.m.
NEDg Description generation batch_69d938c697f481908a93296ee7f82eae completed April 10, 2026, 5:52 p.m.
NED2 Entity disambiguation (via description) batch_69d940176c988190b7583ce9f2c21898 completed April 10, 2026, 6:23 p.m.
Created at: March 30, 2026, 8:32 p.m.