Triple

T13723786
Position Surface form Disambiguated ID Type / Status
Subject John Esten Cooke E329101 entity
Predicate literaryRegion P1968 FINISHED
Object Virginia E940430 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: Virginia | Statement: [John Esten Cooke, literaryRegion, Virginia]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Virginia
Context triple: [John Esten Cooke, literaryRegion, Virginia]
  • A. Virginia
    Virginia is a small community located within the town of Georgina in Ontario, Canada.
  • B. Virginia
    Virginia is a coastal township in Montserrado County, Liberia, known for its beaches and proximity to the capital, Monrovia.
  • C. Virginia
    Virginia is a character in the classic French farce "Il cappello di paglia di Firenze" ("The Florentine Straw Hat"), around whom part of the play’s romantic and comedic misunderstandings revolve.
  • D. Virginia
    Virginia is the birth name of legendary American country music singer Patsy Cline, renowned for her rich contralto voice and crossover hits in the late 1950s and early 1960s.
  • E. Virginia chosen
    Virginia is a feminine given name of Latin origin, historically associated with notions of virtue and widely used in English-speaking countries.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69de01f52e748190b49c34e10ab8ac34 completed April 14, 2026, 8:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69f79d41d1108190be5193b246845f07 completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:55 p.m.