Triple

T6271532
Position Surface form Disambiguated ID Type / Status
Subject Bojangles E140544 entity
Predicate producer P490 FINISHED
Object Richard May
Richard May is a music producer known for his work on the track "Bojangles."
E613692 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: Richard May | Statement: [Bojangles, producer, Richard May]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard May
Context triple: [Bojangles, producer, Richard May]
  • A. William Ross
    William Ross is an American composer, orchestrator, and conductor known for his work on numerous film scores and collaborations with major Hollywood productions.
  • B. Richard Brown
    Richard Brown is an American writer and illustrator best known as the husband and creative collaborator of author Reeve Lindbergh.
  • C. Philip Woodruff
    Philip Woodruff was the pen name of British civil servant Philip Mason, best known for his influential writings on the British Raj and the Indian Civil Service.
  • D. David Graham
    David Graham is a voice actor best known for narrating the iconic 1984 Super Bowl commercial that introduced Apple’s Macintosh computer.
  • E. Robert M. May
    Robert M. May was a prominent Australian theoretical ecologist and mathematical biologist known for his influential work on population dynamics, chaos theory in ecology, and the mathematical modeling of infectious diseases.
  • 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: Richard May
Triple: [Bojangles, producer, Richard May]
Generated description
Richard May is a music producer known for his work on the track "Bojangles."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Richard May
Target entity description: Richard May is a music producer known for his work on the track "Bojangles."
  • A. William Ross
    William Ross is an American composer, orchestrator, and conductor known for his work on numerous film scores and collaborations with major Hollywood productions.
  • B. Richard Brown
    Richard Brown is an American writer and illustrator best known as the husband and creative collaborator of author Reeve Lindbergh.
  • C. Philip Woodruff
    Philip Woodruff was the pen name of British civil servant Philip Mason, best known for his influential writings on the British Raj and the Indian Civil Service.
  • D. David Graham
    David Graham is a voice actor best known for narrating the iconic 1984 Super Bowl commercial that introduced Apple’s Macintosh computer.
  • E. Robert M. May
    Robert M. May was a prominent Australian theoretical ecologist and mathematical biologist known for his influential work on population dynamics, chaos theory in ecology, and the mathematical modeling of infectious diseases.
  • 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_69c008cabc4081909723e2547c9d6cc0 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c063bb340c8190ab81b249cefa91ca completed March 22, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7005e8c2c81909729f7ab3ae0287d completed March 27, 2026, 10:10 p.m.
NEDg Description generation batch_69c7063ab9188190be0cd1eaac3b00be completed March 27, 2026, 10:35 p.m.
NED2 Entity disambiguation (via description) batch_69c70698970c81908bd894882964ccec completed March 27, 2026, 10:37 p.m.
Created at: March 22, 2026, 4:25 p.m.