Triple

T6680518
Position Surface form Disambiguated ID Type / Status
Subject Aikaterine E151966 entity
Predicate hasVariant P455 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: [Aikaterine, hasVariant, Catherine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catherine
Context triple: [Aikaterine, hasVariant, 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_69c687f830bc81909eb8b04dbb8450b1 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6b11df8d88190bf19fcb4e7a0bdb3 completed March 27, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6f7a9fda4819096d4bd3e8133cecb completed March 27, 2026, 9:33 p.m.
Created at: March 27, 2026, 2:04 p.m.