Triple

T7554267
Position Surface form Disambiguated ID Type / Status
Subject Computer Entrepreneur Award E178618 entity
Predicate hasRecipient P108 FINISHED
Object Bill Gates E20772 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: Bill Gates | Statement: [Computer Entrepreneur Award, hasRecipient, Bill Gates]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bill Gates
Context triple: [Computer Entrepreneur Award, hasRecipient, Bill Gates]
  • A. Bill Gates chosen
    Bill Gates is an American business magnate, software pioneer, and philanthropist who co-created the Windows operating system and later co-founded one of the world’s largest charitable foundations.
  • B. Willard Gates
    Willard Gates is a scheming, morally corrupt businessman and secondary antagonist in the 1942 film noir "This Gun for Hire."
  • C. Steve Ballmer
    Steve Ballmer is an American businessman and former Microsoft CEO known for his energetic leadership style and ownership of the NBA’s Los Angeles Clippers.
  • D. Paul Allen
    Paul Allen was an American entrepreneur, investor, and philanthropist best known as the co-founder of Microsoft alongside Bill Gates.
  • E. Mike Lynch
    Mike Lynch is a collegiate athletics administrator best known for leading the athletic department at Babson College.
  • 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_69c69f2da22c8190a50942ac20af70e8 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f8b990148190b26a3a262cf538b3 completed March 27, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69c856be6e1c8190ba292d4d9cf1f37f completed March 28, 2026, 10:31 p.m.
Created at: March 27, 2026, 3:49 p.m.