Triple

T9578544
Position Surface form Disambiguated ID Type / Status
Subject Training Day (TV series) E231109 entity
Predicate mainCharacter P1183 FINISHED
Object Kyle Craig
Kyle Craig is the rookie LAPD officer who partners with a morally ambiguous veteran detective in the television adaptation of "Training Day."
 E809287 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 Craig | Statement: [Training Day (TV series), mainCharacter, Kyle Craig]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kyle Craig
Context triple: [Training Day (TV series), mainCharacter, Kyle Craig]
  • A. Kyle Moats
    Kyle Moats is an American college athletics administrator who serves as the athletic director at Missouri State University, overseeing its sports programs including the men's basketball team.
  • B. Corey Gaines
    Corey Gaines is an American basketball coach and former player best known for leading the WNBA’s Phoenix Mercury to a championship as head coach.
  • C. Aaron McKie
    Aaron McKie is a former American NBA guard and Sixth Man of the Year who later became a college basketball coach.
  • D. Matthew Skemp
    Matthew Skemp is a musician best known as a member of the experimental indie rock band Volcano Choir.
  • E. Alexander Kirkland
    Alexander Kirkland was an American actor active in the early to mid-20th century, known for his work on stage and in films.
  • 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 Craig
Triple: [Training Day (TV series), mainCharacter, Kyle Craig]
Generated description
Kyle Craig is the rookie LAPD officer who partners with a morally ambiguous veteran detective in the television adaptation of "Training Day."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kyle Craig
Target entity description: Kyle Craig is the rookie LAPD officer who partners with a morally ambiguous veteran detective in the television adaptation of "Training Day."
  • A. Kyle Moats
    Kyle Moats is an American college athletics administrator who serves as the athletic director at Missouri State University, overseeing its sports programs including the men's basketball team.
  • B. Corey Gaines
    Corey Gaines is an American basketball coach and former player best known for leading the WNBA’s Phoenix Mercury to a championship as head coach.
  • C. Aaron McKie
    Aaron McKie is a former American NBA guard and Sixth Man of the Year who later became a college basketball coach.
  • D. Matthew Skemp
    Matthew Skemp is a musician best known as a member of the experimental indie rock band Volcano Choir.
  • E. Alexander Kirkland
    Alexander Kirkland was an American actor active in the early to mid-20th century, known for his work on stage and in films.
  • 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_69ca848091c48190bc313d6620d09555 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd99aece1081908287e03106de020f completed April 1, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1615d093c8190940037e9e0842db5 completed April 4, 2026, 7:07 p.m.
NEDg Description generation batch_69d161e6a1308190932c8386e1c24f2e completed April 4, 2026, 7:09 p.m.
NED2 Entity disambiguation (via description) batch_69d165a8c80081909e4d0837cbaabf95 completed April 4, 2026, 7:25 p.m.
Created at: March 30, 2026, 8:05 p.m.