Triple

T4716927
Position Surface form Disambiguated ID Type / Status
Subject John Cleese E104665 entity
Predicate spouse P13 FINISHED
Object Jennifer Wade E203180 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: Jennifer Wade | Statement: [John Cleese, spouse, Jennifer Wade]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer Wade
Context triple: [John Cleese, spouse, Jennifer Wade]
  • A. Jennifer Wade chosen
    Jennifer Wade is a British jewelry designer and former model best known as the fourth wife of comedian and actor John Cleese.
  • B. Sydney Ellen Wade
    Sydney Ellen Wade is a fictional, idealistic environmental lobbyist who becomes the romantic interest of the U.S. president in the film "The American President."
  • C. Kay Medford
    Kay Medford was an American stage and screen actress best known for her Tony- and Oscar-nominated portrayal of Fanny Brice’s mother in the musical and film "Funny Girl."
  • D. Jennifer Winkley
    Jennifer Winkley is known as the former spouse of acclaimed American novelist Cormac McCarthy.
  • E. Jenna Ward
    Jenna Ward is the sister of American actress Sela Ward, who is known for her work in film and television.
  • 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_69bd43ec4a348190bc41afae43375e71 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd640a32ec8190850146957885c3cf completed March 20, 2026, 3:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69bfaf26c0e481909f54973d30da3ef4 completed March 22, 2026, 8:58 a.m.
Created at: March 20, 2026, 1:18 p.m.