Triple

T23260008
Position Surface form Disambiguated ID Type / Status
Subject Wendy E581976 entity
Predicate hasNotableBearer P458 FINISHED
Object Wendy Cope NE NERFINISHED

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: Wendy Cope | Statement: [Wendy, hasNotableBearer, Wendy Cope]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wendy Cope
Context triple: [Wendy, hasNotableBearer, Wendy Cope]
  • A. Wendy Cope chosen
    Wendy Cope is a contemporary English poet known for her witty, accessible verse and humorous yet incisive reflections on modern relationships and everyday life.
  • B. Carole Doughty
    Carole Doughty is known as the first wife of American character actor Charles Durning.
  • C. Kay Nesbitt
    Kay Nesbitt is the central protagonist of the comic strip "Married Life," around whom the series’ domestic and humorous storylines revolve.
  • D. Jo Shapcott
    Jo Shapcott is a contemporary British poet known for her inventive, often surreal verse and multiple major awards, including the Costa Poetry Award.
  • E. Prunella Gee
    Prunella Gee is a British actress known for her film, television, and stage work, particularly in British productions of the 1970s and 1980s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e246079f58819085eaa9c260906880 completed April 17, 2026, 2:39 p.m.
NER Named-entity recognition batch_69f194c7ec148190b01fd215a0c1daa1 completed April 29, 2026, 5:19 a.m.
Created at: April 17, 2026, 4:11 p.m.