Triple

T10408836
Position Surface form Disambiguated ID Type / Status
Subject Thomas Carlyle Ford E245334 entity
Predicate spouse P13 FINISHED
Object Richard Buckley E300560 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: Richard Buckley | Statement: [Thomas Carlyle Ford, spouse, Richard Buckley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Richard Buckley
Context triple: [Thomas Carlyle Ford, spouse, Richard Buckley]
  • A. Richard Buckley chosen
    Richard Buckley was an American fashion journalist and editor, best known for his long career at magazines like Vogue and Vanity Fair and his decades-long partnership with designer Tom Ford.
  • B. Rob Buckley
    Rob Buckley is a relatively obscure individual whose name is notably associated with the surname Buckley but who has no widely recognized public profile.
  • C. Michael Buckley
    Michael Buckley is a common name shared by several notable individuals, including authors, entertainers, and public figures across different fields.
  • D. David Buckley
    David Buckley is a British film and television composer known for scoring numerous Hollywood productions, including action and thriller films.
  • E. Rufus Buckley
    Rufus Buckley is an ambitious and politically driven prosecutor in John Grisham’s legal thriller "A Time to Kill."
  • 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_69d381be340c8190b05998703d42d224 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9faa97c819092cadedadabe26bf completed April 7, 2026, 11:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69d94af4ee6881909a36ee1a06a9d3e2 completed April 10, 2026, 7:09 p.m.
Created at: April 6, 2026, 12:09 p.m.