Triple

T18360731
Position Surface form Disambiguated ID Type / Status
Subject Harve Presnell E439907 entity
Predicate familyName P18 FINISHED
Object Presnell
Presnell is a surname most notably associated with American actor and singer Harve Presnell, known for his work in film, television, and musical theatre.
 E1320281 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: Presnell | Statement: [Harve Presnell, familyName, Presnell]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Presnell
Context triple: [Harve Presnell, familyName, Presnell]
  • A. Conerly
    Conerly is a surname most notably associated with Charlie Conerly, a prominent mid-20th-century American football quarterback.
  • B. Bresnahan
    Bresnahan is a surname most notably associated with early 20th-century American baseball player and Hall of Fame catcher Roger Bresnahan.
  • C. Snelling
    Snelling is a surname of English origin borne by various notable individuals, including military figures and public officials.
  • D. Prendergast
    Prendergast is an Irish surname historically associated with families of Norman origin that settled in Ireland.
  • E. Payette
    Payette is a French-Canadian surname most notably associated with Julie Payette, an engineer, astronaut, and former Governor General of 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: Presnell
Triple: [Harve Presnell, familyName, Presnell]
Generated description
Presnell is a surname most notably associated with American actor and singer Harve Presnell, known for his work in film, television, and musical theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Presnell
Target entity description: Presnell is a surname most notably associated with American actor and singer Harve Presnell, known for his work in film, television, and musical theatre.
  • A. Conerly
    Conerly is a surname most notably associated with Charlie Conerly, a prominent mid-20th-century American football quarterback.
  • B. Bresnahan
    Bresnahan is a surname most notably associated with early 20th-century American baseball player and Hall of Fame catcher Roger Bresnahan.
  • C. Snelling
    Snelling is a surname of English origin borne by various notable individuals, including military figures and public officials.
  • D. Prendergast
    Prendergast is an Irish surname historically associated with families of Norman origin that settled in Ireland.
  • E. Payette
    Payette is a French-Canadian surname most notably associated with Julie Payette, an engineer, astronaut, and former Governor General of 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_69d8b918221c8190a9f7b563d64ac677 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e516db045c8190b20c209225a53b9a completed April 19, 2026, 5:54 p.m.
NED1 Entity disambiguation (via context triple) batch_6a03cc328b108190b28416eb5bfb0b4f completed May 13, 2026, 12:56 a.m.
NEDg Description generation batch_6a03d2a6e7648190881a140d42ae7e86 completed May 13, 2026, 1:23 a.m.
NED2 Entity disambiguation (via description) batch_6a03d40ba5ec81909371d4134a88101d completed May 13, 2026, 1:29 a.m.
Created at: April 10, 2026, 10:37 a.m.