Triple

T6643344
Position Surface form Disambiguated ID Type / Status
Subject Buckley E150638 entity
Predicate hasNotableBearer P458 FINISHED
Object Michael J. Buckley E614884 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: Michael J. Buckley | Statement: [Buckley, hasNotableBearer, Michael J. Buckley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael J. Buckley
Context triple: [Buckley, hasNotableBearer, Michael J. Buckley]
  • A. Michael Buckley chosen
    Michael Buckley is a common name shared by several notable individuals, including authors, entertainers, and public figures across different fields.
  • 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. David J. Burke
    David J. Burke is a television producer and writer best known for his work as an executive producer on the science fiction series SeaQuest DSV.
  • D. Richard Buckley
    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.
  • E. David Buckley
    David Buckley is a British film and television composer known for scoring numerous Hollywood productions, including action and thriller films.
  • 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_69c687f1a3048190828b7342f7125d5c completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6aff749d48190bf24d448daf13bc7 completed March 27, 2026, 4:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69c79c73b2d88190b902b91889eebecd completed March 28, 2026, 9:16 a.m.
Created at: March 27, 2026, 2 p.m.