Triple

T14640414
Position Surface form Disambiguated ID Type / Status
Subject Drunk Parents E343705 entity
Predicate mainCharacter P1183 FINISHED
Object Nancy Teagarten
Nancy Teagarten is a central character in the comedy film "Drunk Parents," around whom much of the movie’s family and financial chaos revolves.
 E1306253 NE FINISHED

How this triple was built (3 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.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Nancy Teagarten
Context triple: [Drunk Parents, mainCharacter, Nancy Teagarten]
  • A. Nancy Fallon
    Nancy Fallon is the teenage protagonist of the film "Teenage Rebel," whose struggles with family and identity drive the story’s emotional conflict.
  • B. Suzy Welch
    Suzy Welch is an American author, television commentator, and business journalist known for her work on management and leadership, including co-authoring books with former GE CEO Jack Welch.
  • C. Constance Towers
    Constance Towers is an American actress and singer known for her work in film, television, and on Broadway, including notable roles in "The Naked Kiss" and the soap opera "General Hospital."
  • D. Kathy Hilton
    Kathy Hilton is an American socialite, fashion designer, and television personality, best known as the matriarch of the Hilton family and for her appearances on reality TV, including "The Real Housewives of Beverly Hills."
  • E. Linda Hurley
    Linda Hurley is an Australian community advocate and former viceregal consort, known for her role as the wife of General David Hurley, the 27th Governor-General of Australia.
  • 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: Nancy Teagarten
Triple: [Drunk Parents, mainCharacter, Nancy Teagarten]
Generated description
Nancy Teagarten is a central character in the comedy film "Drunk Parents," around whom much of the movie’s family and financial chaos revolves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Nancy Teagarten
Target entity description: Nancy Teagarten is a central character in the comedy film "Drunk Parents," around whom much of the movie’s family and financial chaos revolves.
  • A. Nancy Fallon
    Nancy Fallon is the teenage protagonist of the film "Teenage Rebel," whose struggles with family and identity drive the story’s emotional conflict.
  • B. Suzy Welch
    Suzy Welch is an American author, television commentator, and business journalist known for her work on management and leadership, including co-authoring books with former GE CEO Jack Welch.
  • C. Constance Towers
    Constance Towers is an American actress and singer known for her work in film, television, and on Broadway, including notable roles in "The Naked Kiss" and the soap opera "General Hospital."
  • D. Kathy Hilton
    Kathy Hilton is an American socialite, fashion designer, and television personality, best known as the matriarch of the Hilton family and for her appearances on reality TV, including "The Real Housewives of Beverly Hills."
  • E. Linda Hurley
    Linda Hurley is an Australian community advocate and former viceregal consort, known for her role as the wife of General David Hurley, the 27th Governor-General of Australia.
  • F. None of above. chosen

Provenance (4 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_69d822e1a2cc81908e5bb93cf61ce3cc completed April 9, 2026, 10:06 p.m.
NED1 Entity disambiguation (via context triple) batch_6a037c1ca5408190ba46c0ce5515062a completed May 12, 2026, 7:14 p.m.
NEDg Description generation batch_6a037ca6f5888190b0ed34777aae862f completed May 12, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_6a037d319be48190b01a1b8d1f239078 completed May 12, 2026, 7:19 p.m.
Created at: April 10, 2026, 1:26 a.m.