Triple

T16931764
Position Surface form Disambiguated ID Type / Status
Subject Lady Louisa Carteret E410726 entity
Predicate mother P120 FINISHED
Object Frances Worsley E409286 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: Frances Worsley | Statement: [Lady Louisa Carteret, mother, Frances Worsley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Frances Worsley
Context triple: [Lady Louisa Carteret, mother, Frances Worsley]
  • A. Frances Worsley chosen
    Frances Worsley was an 18th-century English noblewoman best known as the wife of John Carteret, 2nd Earl Granville, a prominent British statesman.
  • B. Katharine Worsley
    Katharine Worsley is a member of the British royal family who became the Duchess of Kent through her marriage to Prince Edward, Duke of Kent.
  • C. Margaret Wyborn
    Margaret Wyborn is the efficient and often exasperated nurse and office assistant who works for Dr. John Becker in the television sitcom "Becker."
  • D. Letitia Cropley
    Letitia Cropley is an eccentric parishioner in the British sitcom "The Vicar of Dibley," best known for her bizarre and unappetizing culinary creations.
  • E. Mary Rawlinson
    Mary Rawlinson is a scholar and academic known for her work in philosophy, bioethics, and feminist theory.
  • 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_69d886c886688190967be07322597ac9 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3cf25a6dc8190a2b9d9c4d2adc5fd completed April 18, 2026, 6:36 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00d45c32a08190970137790d08f499 completed May 10, 2026, 6:54 p.m.
Created at: April 10, 2026, 5:30 a.m.