Triple

T14213702
Position Surface form Disambiguated ID Type / Status
Subject Future Man E352293 entity
Predicate creator P184 FINISHED
Object Kyle Hunter
Kyle Hunter is a television writer and producer best known for co-creating the sci-fi comedy series "Future Man."
E1086057 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: Kyle Hunter | Statement: [Future Man, creator, Kyle Hunter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kyle Hunter
Context triple: [Future Man, creator, Kyle Hunter]
  • A. John Cutter
    John Cutter is the tough, resourceful airline security expert portrayed by Wesley Snipes in the 1992 action thriller film "Passenger 57."
  • B. Krieger Newman
    Krieger Newman is a relative of American professional stock car racing driver Ryan Newman.
  • C. Peter Keightley
    Peter Keightley is an evolutionary geneticist known for his work on the genetic basis of quantitative traits and the effects of deleterious mutations on genome evolution.
  • D. Alex Datcher
    Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
  • E. Jason Seaver
    Jason Seaver is the wisecracking psychiatrist father and central figure of the 1980s American sitcom "Growing Pains."
  • 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: Kyle Hunter
Triple: [Future Man, creator, Kyle Hunter]
Generated description
Kyle Hunter is a television writer and producer best known for co-creating the sci-fi comedy series "Future Man."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kyle Hunter
Target entity description: Kyle Hunter is a television writer and producer best known for co-creating the sci-fi comedy series "Future Man."
  • A. John Cutter
    John Cutter is the tough, resourceful airline security expert portrayed by Wesley Snipes in the 1992 action thriller film "Passenger 57."
  • B. Krieger Newman
    Krieger Newman is a relative of American professional stock car racing driver Ryan Newman.
  • C. Peter Keightley
    Peter Keightley is an evolutionary geneticist known for his work on the genetic basis of quantitative traits and the effects of deleterious mutations on genome evolution.
  • D. Alex Datcher
    Alex Datcher is an American actress best known for her role as a flight attendant alongside Wesley Snipes in the 1992 action film "Passenger 57."
  • E. Jason Seaver
    Jason Seaver is the wisecracking psychiatrist father and central figure of the 1980s American sitcom "Growing Pains."
  • 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_69d8278a06e481908b5d6af0a8afe737 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de620f07bc81909212dcd1c91b5f95 completed April 14, 2026, 3:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd1959f3d481909c15730bbd6f4748 completed May 7, 2026, 10:59 p.m.
NEDg Description generation batch_69fd1a88fd948190b5d78a4ca4acdb94 completed May 7, 2026, 11:04 p.m.
NED2 Entity disambiguation (via description) batch_69fd1b2ed7748190b3f787f1b64c8831 completed May 7, 2026, 11:07 p.m.
Created at: April 10, 2026, 1:06 a.m.