Triple

T20110868
Position Surface form Disambiguated ID Type / Status
Subject Alexander Waugh E490324 entity
Predicate grandmother P3524 FINISHED
Object Laura Waugh 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: Laura Waugh | Statement: [Alexander Waugh, grandmother, Laura Waugh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laura Waugh
Context triple: [Alexander Waugh, grandmother, Laura Waugh]
  • A. Laura Waugh chosen
    Laura Waugh was the mother of English journalist and satirist Auberon Waugh and a member of the literary Waugh family.
  • B. Anna Wharton
    Anna Wharton was the wife of American politician and diplomat Frederick William Seward, connecting her to a prominent 19th-century U.S. political family.
  • C. Pippa Bennett-Warner
    Pippa Bennett-Warner is a British actress known for her work in television, film, and theatre, including prominent roles in period dramas and contemporary series.
  • D. Elizabeth Dauncey
    Elizabeth Dauncey was the wife of American screenwriter Waldemar Young, known primarily through her marriage to this prominent Hollywood figure.
  • E. Elizabeth Dauncey
    Elizabeth Dauncey was the daughter of Sir Thomas More and a learned Tudor gentlewoman known for her humanist education and correspondence.
  • 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_69da62636cc08190982cc71733a17b8d completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e666e0180c8190adeead0e60a099b0 completed April 20, 2026, 5:48 p.m.
Created at: April 11, 2026, 11:29 p.m.