Triple

T8156169
Position Surface form Disambiguated ID Type / Status
Subject Their Finest E190454 entity
Predicate mainCharacter P1183 FINISHED
Object Tom Buckley E622336 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: Tom Buckley | Statement: [Their Finest, mainCharacter, Tom Buckley]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom Buckley
Context triple: [Their Finest, mainCharacter, Tom Buckley]
  • A. Tom Buckley chosen
    Tom Buckley is a relatively common personal name shared by multiple individuals, including professionals in fields such as journalism, sports, and politics.
  • B. Michael Buckley
    Michael Buckley is a common name shared by several notable individuals, including authors, entertainers, and public figures across different fields.
  • C. 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.
  • D. Patrick Buckley
    Patrick Buckley is a personal name shared by multiple individuals, including various professionals and public figures across fields such as politics, sports, and business.
  • E. James Buckley
    James Buckley is an English actor and comedian best known for playing Jay Cartwright in the British sitcom "The Inbetweeners."
  • 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_69ca82bfeb6481909d07b91b5cf69f59 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb44d8a37481909397b5cc321b94be completed March 31, 2026, 3:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cde71b7688819096b2d30a37a8a00b completed April 2, 2026, 3:48 a.m.
Created at: March 30, 2026, 5:37 p.m.