Triple

T2689360
Position Surface form Disambiguated ID Type / Status
Subject Kate E57561 entity
Predicate shortFormOf P43 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: [Kate, shortFormOf, Catherine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Catherine
Context triple: [Kate, shortFormOf, 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 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.
  • D. Louisa
    Louisa is the middle name of Katharine Louisa Stanley, a 19th-century English writer and member of the prominent Stanley family.
  • 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_69ab4a5028388190a36f3baf1588309e completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd9f380d48190953529d23688a328 completed March 7, 2026, 7:55 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf5e85bc81908ba1b1968cfa440a completed March 10, 2026, 5:42 a.m.
Created at: March 6, 2026, 9:54 p.m.