Triple

T999262
Position Surface form Disambiguated ID Type / Status
Subject Lady Randolph Churchill E21566 entity
Predicate givenName P17 FINISHED
Object Jennie E47548 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: Jennie | Statement: [Lady Randolph Churchill, givenName, Jennie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennie
Context triple: [Lady Randolph Churchill, givenName, Jennie]
  • A. Hannah Jeter
    Hannah Jeter is an American fashion model and television host best known for her work with Sports Illustrated Swimsuit Issue and for co-hosting "Project Runway: Junior."
  • B. Sarah Jane Emery
    Sarah Jane Emery was the wife of Hannibal Hamlin, who served as vice president of the United States under Abraham Lincoln.
  • C. Jennifer chosen
    Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
  • D. Chloe Wojin
    Chloe Wojin is the daughter of Google co-founder Sergey Brin and biotech entrepreneur Anne Wojcicki.
  • E. Tina
    Tina is the nickname of Tina Fey, an American comedian, writer, actress, and producer best known for her work on Saturday Night Live and 30 Rock.
  • 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_69a493c476b48190b41fc5e793171cc6 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b4e3d8b081908e536928e7d6199d completed March 1, 2026, 9:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac2a1aab68819091537958818fce48 completed March 7, 2026, 1:37 p.m.
Created at: March 1, 2026, 7:41 p.m.