Triple

T7178361
Position Surface form Disambiguated ID Type / Status
Subject Catherine Melville E167376 entity
Predicate givenName P17 FINISHED
Object Catherine E8723 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: Catherine | Statement: [Catherine Melville, givenName, Catherine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catherine
Context triple: [Catherine Melville, givenName, Catherine]
  • A. Catherine chosen
    Catherine is a feminine given name of Greek origin, derived from Aikaterine and widely used in various forms across many cultures.
  • B. Catherine
    "Catherine" is an early satirical novel by William Makepeace Thackeray that parodies the popular crime and Newgate novels of his time.
  • C. Catherine Hyde
    Catherine Hyde, later Catherine Douglas, Duchess of Queensberry, was an 18th-century British noblewoman and socialite known for her influential role in London high society.
  • D. Georgiana
    Georgiana is a feminine given name of Greek origin, often associated with elegance and historically borne by various notable women in British and European society.
  • E. Louisa
    Louisa is the middle name of Katharine Louisa Stanley, a 19th-century English writer and member of the prominent Stanley family.
  • 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_69c6888a7c548190a3d39b52a393080f completed March 27, 2026, 1:39 p.m.
NER Named-entity recognition batch_69c6e8b8241081908edb5b5a5c35d4d3 completed March 27, 2026, 8:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7b92f3d748190ab2a3694420b5724 completed March 28, 2026, 11:19 a.m.
Created at: March 27, 2026, 2:49 p.m.