Triple

T11956621
Position Surface form Disambiguated ID Type / Status
Subject Younger E284568 entity
Predicate executiveProducer P7225 FINISHED
Object Larry W. Jones
Larry W. Jones is a television executive best known for his leadership roles at major cable networks, including serving as president of TV Land.
 E1037416 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: Larry W. Jones | Statement: [Younger, executiveProducer, Larry W. Jones]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Larry W. Jones
Context triple: [Younger, executiveProducer, Larry W. Jones]
  • A. Richard T. Jones
    Richard T. Jones is an American actor known for his roles in film and television, including prominent performances in dramas and thrillers.
  • B. James L. Wilmeth
    James L. Wilmeth was an American government official who served as a senior federal financial administrator in the early 20th century.
  • C. Todd R. Jones
    Todd R. Jones is a writer known for his work on the animated film "Rio."
  • D. Kent L. Wakeford
    Kent L. Wakeford was an American cinematographer known for his work on influential 1970s films, particularly in collaboration with director Martin Scorsese.
  • E. Hugh G. Jones
    Hugh G. Jones was an architect known for his role in designing Toronto’s historic Union Station.
  • 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: Larry W. Jones
Triple: [Younger, executiveProducer, Larry W. Jones]
Generated description
Larry W. Jones is a television executive best known for his leadership roles at major cable networks, including serving as president of TV Land.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Larry W. Jones
Target entity description: Larry W. Jones is a television executive best known for his leadership roles at major cable networks, including serving as president of TV Land.
  • A. Richard T. Jones
    Richard T. Jones is an American actor known for his roles in film and television, including prominent performances in dramas and thrillers.
  • B. James L. Wilmeth
    James L. Wilmeth was an American government official who served as a senior federal financial administrator in the early 20th century.
  • C. Todd R. Jones
    Todd R. Jones is a writer known for his work on the animated film "Rio."
  • D. Kent L. Wakeford
    Kent L. Wakeford was an American cinematographer known for his work on influential 1970s films, particularly in collaboration with director Martin Scorsese.
  • E. Hugh G. Jones
    Hugh G. Jones was an architect known for his role in designing Toronto’s historic Union Station.
  • 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_69d6ab2db38c8190b1f0ed6663ef8ada completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d90366fda8819083168c93abad27d4 completed April 10, 2026, 2:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69f72654dc88819095bc1ce23dfee4df completed May 3, 2026, 10:41 a.m.
NEDg Description generation batch_69f727512c94819091985c7942f40b31 completed May 3, 2026, 10:45 a.m.
NED2 Entity disambiguation (via description) batch_69f72b77d650819092c02f6488b2cfb2 completed May 3, 2026, 11:03 a.m.
Created at: April 8, 2026, 9:45 p.m.