Triple

T258624
Position Surface form Disambiguated ID Type / Status
Subject Robert Harvard E5491 entity
Predicate relative P37 FINISHED
Object Katherine Rogers E17741 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: Katherine Rogers | Statement: [Robert Harvard, relative, Katherine Rogers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Katherine Rogers
Context triple: [Robert Harvard, relative, Katherine Rogers]
  • A. Katherine Rogers chosen
    Katherine Rogers was the mother of John Harvard, the English clergyman whose bequest helped found Harvard College in colonial Massachusetts.
  • B. Lisa Rogers
    Lisa Rogers is a member of the Rogers family, known as the daughter of Canadian businessman and media magnate Ted Rogers.
  • C. Karen Richards
    Karen Richards is a key character in the classic film "All About Eve," a theater insider whose friendship and decisions help drive the story’s backstage drama and betrayal.
  • D. Melinda Rogers
    Melinda Rogers is a Canadian business executive and member of the Rogers family, known for her leadership roles within Rogers Communications.
  • E. Katherine Clifton
    Katherine Clifton is a central character in Michael Ondaatje's novel "The English Patient," known for her tragic love affair and its far-reaching consequences during World War II.
  • 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_69a2580a64ac8190ad76e34bb0715b5e completed Feb. 28, 2026, 2:50 a.m.
NER Named-entity recognition batch_69a25d71a10c8190894c86e7a67c5974 completed Feb. 28, 2026, 3:13 a.m.
NED1 Entity disambiguation (via context triple) batch_69acc5e4ba188190876eea46a4f6ec1c completed March 8, 2026, 12:42 a.m.
Created at: Feb. 28, 2026, 2:55 a.m.