Triple

T21587173
Position Surface form Disambiguated ID Type / Status
Subject A Time for Love E532679 entity
Predicate hasNotablePerformer P17435 FINISHED
Object Bill Mays
Bill Mays is an American jazz pianist, composer, and arranger known for his lyrical style and extensive work as both a bandleader and sought-after sideman.
 E1491036 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: Bill Mays | Statement: [A Time for Love, hasNotablePerformer, Bill Mays]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bill Mays
Context triple: [A Time for Love, hasNotablePerformer, Bill Mays]
  • A. Paul Ebersold
    Paul Ebersold is a music producer known for his work on various rock and alternative records.
  • B. W. Max Finley
    W. Max Finley was a prominent Chattanooga businessman and civic leader whose contributions to the community led to the city’s main football stadium being named in his honor.
  • C. Jack McClendon
    Jack McClendon is an actor known for his role in the film "Hellgate."
  • D. Bill Klem
    Bill Klem was a pioneering Major League Baseball umpire, often called the "father of modern umpiring," known for his long career and influential role in shaping officiating standards.
  • E. Tom Howe
    Tom Howe is a British composer best known for his work on film and television scores, including the acclaimed series "Ted Lasso."
  • 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: Bill Mays
Triple: [A Time for Love, hasNotablePerformer, Bill Mays]
Generated description
Bill Mays is an American jazz pianist, composer, and arranger known for his lyrical style and extensive work as both a bandleader and sought-after sideman.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bill Mays
Target entity description: Bill Mays is an American jazz pianist, composer, and arranger known for his lyrical style and extensive work as both a bandleader and sought-after sideman.
  • A. Paul Ebersold
    Paul Ebersold is a music producer known for his work on various rock and alternative records.
  • B. W. Max Finley
    W. Max Finley was a prominent Chattanooga businessman and civic leader whose contributions to the community led to the city’s main football stadium being named in his honor.
  • C. Jack McClendon
    Jack McClendon is an actor known for his role in the film "Hellgate."
  • D. Bill Klem
    Bill Klem was a pioneering Major League Baseball umpire, often called the "father of modern umpiring," known for his long career and influential role in shaping officiating standards.
  • E. Tom Howe
    Tom Howe is a British composer best known for his work on film and television scores, including the acclaimed series "Ted Lasso."
  • 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_69e0c46251648190876f0427cf2d321b completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69eeeb6137fc8190840b7c1275e62a1d completed April 27, 2026, 4:51 a.m.
NED1 Entity disambiguation (via context triple) batch_6a09f67f08208190a1633fd2a28e2fa2 completed May 17, 2026, 5:10 p.m.
NEDg Description generation batch_6a09f6fc3d7081909edf8cc575b6293e completed May 17, 2026, 5:12 p.m.
NED2 Entity disambiguation (via description) batch_6a09f79098e48190acdcad615098c55a completed May 17, 2026, 5:14 p.m.
Created at: April 16, 2026, 6:31 p.m.