Triple

T10817309
Position Surface form Disambiguated ID Type / Status
Subject Ross Perot E255264 entity
Predicate hasChild P369 FINISHED
Object Nancy Perot E255264 NE FINISHED

How this triple was built (2 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: Nancy Perot | Statement: [Ross Perot, hasChild, Nancy Perot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nancy Perot
Context triple: [Ross Perot, hasChild, Nancy Perot]
  • A. Nancy Perot chosen
    Nancy Perot is a member of the prominent Perot family, known as the sister of businessman Ross Perot Jr. and daughter of the late billionaire and former U.S. presidential candidate Ross Perot.
  • B. Margot Birmingham Perot
    Margot Birmingham Perot is an American philanthropist known for her extensive charitable work in health care, education, and the arts, and as the wife of the late businessman and presidential candidate Ross Perot.
  • C. Suzanne Perot
    Suzanne Perot is a member of the prominent Perot family, known for its significant influence in American business, philanthropy, and politics.
  • D. Katherine Perot
    Katherine Perot is a member of the prominent Perot family, known for its significant influence in American business and philanthropy.
  • E. Ron Rice
    Ron Rice was an influential American experimental filmmaker associated with New York’s underground cinema scene in the early 1960s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d6aa8081448190a9324184f2bd1c26 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d733eea03c8190a68f4d4f89f497a2 completed April 9, 2026, 5:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69de855799748190b51745a198daa8d0 completed April 14, 2026, 6:20 p.m.
Created at: April 8, 2026, 9:18 p.m.