Triple

T13507561
Position Surface form Disambiguated ID Type / Status
Subject Get Shorty E321051 entity
Predicate mainCharacter P1183 FINISHED
Object Bo Catlett
Bo Catlett is a powerful and smooth-talking Hollywood-connected loan shark and film producer in Elmore Leonard’s crime novel and its film adaptation "Get Shorty."
 E1045615 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: Bo Catlett | Statement: [Get Shorty, mainCharacter, Bo Catlett]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bo Catlett
Context triple: [Get Shorty, mainCharacter, Bo Catlett]
  • A. Walter Catlett
    Walter Catlett was an American character actor and comedian known for his scene-stealing comic roles in classic Hollywood films of the 1930s and 1940s.
  • B. Edward Ellett
    Edward Ellett was an early settler and prominent local figure after whom the town of Ellettsville, Indiana, was named.
  • C. John Crowell
    John Crowell is a person notable enough to be recognized as a significant bearer of the surname Crowell.
  • D. P. M. Blodgett
    P. M. Blodgett was an early settler and prominent local figure in Oregon after whom the community of Blodgett was named.
  • E. Frank Johnston
    Frank Johnston was a Canadian landscape painter best known as one of the original members of the Group of Seven, a pioneering modern art movement in early 20th-century Canada.
  • 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: Bo Catlett
Triple: [Get Shorty, mainCharacter, Bo Catlett]
Generated description
Bo Catlett is a powerful and smooth-talking Hollywood-connected loan shark and film producer in Elmore Leonard’s crime novel and its film adaptation "Get Shorty."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bo Catlett
Target entity description: Bo Catlett is a powerful and smooth-talking Hollywood-connected loan shark and film producer in Elmore Leonard’s crime novel and its film adaptation "Get Shorty."
  • A. Walter Catlett
    Walter Catlett was an American character actor and comedian known for his scene-stealing comic roles in classic Hollywood films of the 1930s and 1940s.
  • B. Edward Ellett
    Edward Ellett was an early settler and prominent local figure after whom the town of Ellettsville, Indiana, was named.
  • C. John Crowell
    John Crowell is a person notable enough to be recognized as a significant bearer of the surname Crowell.
  • D. P. M. Blodgett
    P. M. Blodgett was an early settler and prominent local figure in Oregon after whom the community of Blodgett was named.
  • E. Frank Johnston
    Frank Johnston was a Canadian landscape painter best known as one of the original members of the Group of Seven, a pioneering modern art movement in early 20th-century Canada.
  • 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_69d807629d6c8190998f1b9bb12d2ed0 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf8259a08190ada13c4a3078f07d completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7548e51b881909a3384812556bc3d completed May 3, 2026, 1:58 p.m.
NEDg Description generation batch_69f757108e088190aeec031eccc9aca3 completed May 3, 2026, 2:09 p.m.
NED2 Entity disambiguation (via description) batch_69f757e7322c8190b0e36e8373d42ac4 completed May 3, 2026, 2:12 p.m.
Created at: April 9, 2026, 9:43 p.m.