Triple

T16191450
Position Surface form Disambiguated ID Type / Status
Subject Little Nicky E392950 entity
Predicate starring P1507 FINISHED
Object Peter Dante
Peter Dante is an American actor and comedian best known for his frequent supporting roles in Adam Sandler films such as "Little Nicky," "The Waterboy," and "Grandma's Boy."
 E1199197 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: Peter Dante | Statement: [Little Nicky, starring, Peter Dante]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Peter Dante
Context triple: [Little Nicky, starring, Peter Dante]
  • A. Nik D’Amato
    Nik D’Amato is the central protagonist of the Australian film "Lantana," whose troubled personal life and relationships drive the movie’s intertwined drama.
  • B. Donald Camillieri
    Donald Camillieri is known as the former husband of American actress Kathy Baker.
  • C. Laurence Dworet
    Laurence Dworet is a screenwriter best known for co-writing the 1995 medical disaster film "Outbreak."
  • D. Paul Galdone
    Paul Galdone was a Hungarian-born American illustrator and author best known for his distinctive artwork in numerous classic children's books and fairy tales.
  • E. Dante Lavelli
    Dante Lavelli was a Hall of Fame American football wide receiver best known for his prolific career with the Cleveland Browns in the 1940s and 1950s.
  • 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: Peter Dante
Triple: [Little Nicky, starring, Peter Dante]
Generated description
Peter Dante is an American actor and comedian best known for his frequent supporting roles in Adam Sandler films such as "Little Nicky," "The Waterboy," and "Grandma's Boy."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Peter Dante
Target entity description: Peter Dante is an American actor and comedian best known for his frequent supporting roles in Adam Sandler films such as "Little Nicky," "The Waterboy," and "Grandma's Boy."
  • A. Nik D’Amato
    Nik D’Amato is the central protagonist of the Australian film "Lantana," whose troubled personal life and relationships drive the movie’s intertwined drama.
  • B. Donald Camillieri
    Donald Camillieri is known as the former husband of American actress Kathy Baker.
  • C. Laurence Dworet
    Laurence Dworet is a screenwriter best known for co-writing the 1995 medical disaster film "Outbreak."
  • D. Paul Galdone
    Paul Galdone was a Hungarian-born American illustrator and author best known for his distinctive artwork in numerous classic children's books and fairy tales.
  • E. Dante Lavelli
    Dante Lavelli was a Hall of Fame American football wide receiver best known for his prolific career with the Cleveland Browns in the 1940s and 1950s.
  • 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_69d87f1e49ac8190a311b54d32990576 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e222d5769c8190bbb604bfa095a1a5 completed April 17, 2026, 12:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffff095504819096c36d6c5d131207 completed May 10, 2026, 3:44 a.m.
NEDg Description generation batch_6a0002419cec81909e3cec70968b65a4 completed May 10, 2026, 3:57 a.m.
NED2 Entity disambiguation (via description) batch_6a0002ad960c81909c308a12da9b65d6 completed May 10, 2026, 3:59 a.m.
Created at: April 10, 2026, 5:02 a.m.