Triple

T20022796
Position Surface form Disambiguated ID Type / Status
Subject Gresham College E494903 entity
Predicate hasNotableProfessor P13831 FINISHED
Object Lisa Jardine NE NERFINISHED

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: Lisa Jardine | Statement: [Gresham College, hasNotableProfessor, Lisa Jardine]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lisa Jardine
Context triple: [Gresham College, hasNotableProfessor, Lisa Jardine]
  • A. Lisa Jardine chosen
    Lisa Jardine was a prominent British historian of the Renaissance and early modern period, noted for her work on science, culture, and the history of ideas.
  • B. Patricia Fara
    Patricia Fara is a British historian of science known for her work on the scientific revolution, women in science, and the cultural history of science.
  • C. Claire Tomalin
    Claire Tomalin is a British literary journalist and acclaimed biographer known for her works on figures such as Charles Dickens, Samuel Pepys, and Jane Austen.
  • D. Katharine Bethell
    Katharine Bethell was the wife of pioneering British engineer and steam turbine inventor Charles Algernon Parsons.
  • E. Jacqueline Carlin
    Jacqueline Carlin is an American actress and former model best known for her film and television work in the 1970s and 1980s.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e66288fc18819083833b55c5e069a6 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.