Triple

T9631899
Position Surface form Disambiguated ID Type / Status
Subject Michael E. DeBakey E232827 entity
Predicate familyName P18 FINISHED
Object DeBakey E232827 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: DeBakey | Statement: [Michael E. DeBakey, familyName, DeBakey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: DeBakey
Context triple: [Michael E. DeBakey, familyName, DeBakey]
  • A. Michael E. DeBakey chosen
    Michael E. DeBakey was a pioneering American cardiovascular surgeon and medical innovator whose work revolutionized heart surgery and biomedical research.
  • B. Christiaan Barnard
    Christiaan Barnard was a South African cardiac surgeon best known for performing the world’s first successful human-to-human heart transplant in 1967.
  • C. John Daykin
    John Daykin was a senior Royal Air Force officer who served as Air Officer Commanding-in-Chief of Fighter Command.
  • D. Niels Arestrup
    Niels Arestrup is a French actor and filmmaker renowned for his intense, character-driven performances in both French cinema and international films.
  • E. George Kassabaum
    George Kassabaum was an American architect and co-founder of the global design and architecture firm HOK.
  • 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_69ca848940cc8190b97cec654cb3bb4a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b2783b48190a9929dc3e3cd2956 completed April 1, 2026, 10:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d189fa706c819080e8ac2411f57d93 completed April 4, 2026, 10 p.m.
Created at: March 30, 2026, 8:11 p.m.