Triple

T2595236
Position Surface form Disambiguated ID Type / Status
Subject Katrin E58213 entity
Predicate variantOf P4680 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: [Katrin, variantOf, Catherine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catherine
Context triple: [Katrin, variantOf, 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 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.
  • C. Louisa
    Louisa is the middle name of Katharine Louisa Stanley, a 19th-century English writer and member of the prominent Stanley family.
  • D. Louisa
    Louisa is a fictional character from Jean Toomer’s modernist work "Cane," representing themes of love, memory, and the complexities of African American life in the early 20th-century South.
  • E. Isabel
    Isabel is a feminine given name of Spanish origin, widely used in Spanish- and Portuguese-speaking countries and borne by numerous notable historical and contemporary figures.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd42978f881909f217e7ec9ac3144 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83c3607c81908bb4aceca46c5392 completed March 10, 2026, 2:36 a.m.
Created at: March 6, 2026, 9:49 p.m.