Triple

T10398631
Position Surface form Disambiguated ID Type / Status
Subject Jason Dunham E245084 entity
Predicate hasRelative P367 FINISHED
Object Dan Dunham
Dan Dunham is a relative of U.S. Marine Corps Medal of Honor recipient Jason Dunham.
 E904816 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: Dan Dunham | Statement: [Jason Dunham, hasRelative, Dan Dunham]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Dan Dunham
Context triple: [Jason Dunham, hasRelative, Dan Dunham]
  • A. David Clouse
    David Clouse is an entrepreneur best known as the founder of the vacation rental platform Vrbo (Vacation Rentals by Owner).
  • B. John Diehl
    John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
  • C. David Denny
    David Denny was a 19th-century American pioneer and early settler of Seattle, Washington, who played a key role in the city's founding and development.
  • D. David Ditzel
    David Ditzel is a computer engineer and entrepreneur best known as the founder of Transmeta and for his work on low-power, innovative microprocessor designs.
  • E. Dan Haggerty
    Dan Haggerty was an American actor best known for his portrayal of the gentle mountain man in the film and television series "The Life and Times of Grizzly Adams."
  • 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: Dan Dunham
Triple: [Jason Dunham, hasRelative, Dan Dunham]
Generated description
Dan Dunham is a relative of U.S. Marine Corps Medal of Honor recipient Jason Dunham.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Dan Dunham
Target entity description: Dan Dunham is a relative of U.S. Marine Corps Medal of Honor recipient Jason Dunham.
  • A. David Clouse
    David Clouse is an entrepreneur best known as the founder of the vacation rental platform Vrbo (Vacation Rentals by Owner).
  • B. John Diehl
    John Diehl is an American character actor best known for his role as Detective Larry Zito on the 1980s television series "Miami Vice."
  • C. David Denny
    David Denny was a 19th-century American pioneer and early settler of Seattle, Washington, who played a key role in the city's founding and development.
  • D. David Ditzel
    David Ditzel is a computer engineer and entrepreneur best known as the founder of Transmeta and for his work on low-power, innovative microprocessor designs.
  • E. Dan Haggerty
    Dan Haggerty was an American actor best known for his portrayal of the gentle mountain man in the film and television series "The Life and Times of Grizzly Adams."
  • 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_69d381b5116081908d85227bab6d3c0c completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9d1f2408190beaa8197641c66b4 completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6afdf0c8190924cb14512a89ee8 completed April 18, 2026, 8:16 p.m.
NEDg Description generation batch_69e3f01f9d048190b553184f0f6ce29c completed April 18, 2026, 8:57 p.m.
NED2 Entity disambiguation (via description) batch_69e3f3fef9308190b0354ed436c32e4c completed April 18, 2026, 9:13 p.m.
Created at: April 6, 2026, 12:07 p.m.