Triple

T6222308
Position Surface form Disambiguated ID Type / Status
Subject Brown Sugar E139144 entity
Predicate producer P490 FINISHED
Object Peter Heller
Peter Heller is a British DJ, remixer, and record producer best known for his influential work in house music during the 1990s and 2000s.
 E577722 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: Peter Heller | Statement: [Brown Sugar, producer, Peter Heller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Heller
Context triple: [Brown Sugar, producer, Peter Heller]
  • A. Nathan Barr
    Nathan Barr is an American film and television composer known for his atmospheric scores on projects ranging from horror films to acclaimed series like True Blood and The Americans.
  • B. Jim Holland
    Jim Holland is the husband of Zimbabwean politician and human rights activist Sekai Holland.
  • C. Peter Kerr
    Peter Kerr was a 19th-century architect best known for designing Melbourne's Parliament House, a landmark of Victorian-era civic architecture in Australia.
  • D. Paul Heller
    Paul Heller is a film producer best known for his work on influential cult movies, including the British black comedy "Withnail & I."
  • E. Dan Jewett
    Dan Jewett is an American science teacher known for his brief marriage to billionaire philanthropist and novelist MacKenzie Scott.
  • 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: Peter Heller
Triple: [Brown Sugar, producer, Peter Heller]
Generated description
Peter Heller is a British DJ, remixer, and record producer best known for his influential work in house music during the 1990s and 2000s.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Heller
Target entity description: Peter Heller is a British DJ, remixer, and record producer best known for his influential work in house music during the 1990s and 2000s.
  • A. Nathan Barr
    Nathan Barr is an American film and television composer known for his atmospheric scores on projects ranging from horror films to acclaimed series like True Blood and The Americans.
  • B. Jim Holland
    Jim Holland is the husband of Zimbabwean politician and human rights activist Sekai Holland.
  • C. Peter Kerr
    Peter Kerr was a 19th-century architect best known for designing Melbourne's Parliament House, a landmark of Victorian-era civic architecture in Australia.
  • D. Paul Heller
    Paul Heller is a film producer best known for his work on influential cult movies, including the British black comedy "Withnail & I."
  • E. Dan Jewett
    Dan Jewett is an American science teacher known for his brief marriage to billionaire philanthropist and novelist MacKenzie Scott.
  • 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_69c008aecb0c81909984b48f733ce8ae completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c062bddb688190add53172a7445d01 completed March 22, 2026, 9:44 p.m.
NED1 Entity disambiguation (via context triple) batch_69c20dcc5e788190a510cac6bbad4830 completed March 24, 2026, 4:06 a.m.
NEDg Description generation batch_69c21498cfc0819097d1fa9cb10f7a92 completed March 24, 2026, 4:35 a.m.
NED2 Entity disambiguation (via description) batch_69c215689f288190a54fb3fc7984455a completed March 24, 2026, 4:39 a.m.
Created at: March 22, 2026, 4:22 p.m.