Triple

T4966492
Position Surface form Disambiguated ID Type / Status
Subject Bernard Budiansky E111538 entity
Predicate name P16 FINISHED
Object Bernard Budiansky E111538 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: Bernard Budiansky | Statement: [Bernard Budiansky, name, Bernard Budiansky]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bernard Budiansky
Context triple: [Bernard Budiansky, name, Bernard Budiansky]
  • A. Bernard Budiansky chosen
    Bernard Budiansky was an influential American applied mechanician and Harvard professor known for his pioneering contributions to solid mechanics, structural stability, and material behavior.
  • B. Nathan Furst
    Nathan Furst is an American composer best known for scoring films and television series, particularly in the action and adventure genres.
  • C. Charles Rackoff
    Charles Rackoff is a Canadian computer scientist known for his influential work in cryptography and computational complexity theory.
  • D. Brian Hartnett
    Brian Hartnett is a notable individual distinguished enough in his field or public life to be specifically recognized as a bearer of the Hartnett surname.
  • E. Walter Miller
    Walter Miller was an early 20th-century American film actor known for his work in silent cinema.
  • 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_69bd4419393c819086319a6fe4bf8542 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd71f7ae388190b752770bf577906f completed March 20, 2026, 4:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69be81f13988819097dcd5a65cb1f502 completed March 21, 2026, 11:33 a.m.
Created at: March 20, 2026, 1:32 p.m.