Triple

T14734007
Position Surface form Disambiguated ID Type / Status
Subject Will Murray E346152 entity
Predicate hasWrittenAbout P14097 FINISHED
Object Doc Savage E318151 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: Doc Savage | Statement: [Will Murray, hasWrittenAbout, Doc Savage]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Doc Savage
Context triple: [Will Murray, hasWrittenAbout, Doc Savage]
  • A. Doc Savage chosen
    Doc Savage is a classic pulp adventure hero, a brilliant and physically formidable scientist-explorer known as the "Man of Bronze," who stars in a long-running series of novels and adaptations.
  • B. Hank Morgan
    Hank Morgan is the pragmatic 19th-century American engineer who, transported back to King Arthur’s Britain in Mark Twain’s satirical novel, uses his modern knowledge to upend medieval society.
  • C. Conrad Poole
    Conrad Poole is a South African local government politician who serves as the executive mayor of the Drakenstein Municipality in the Western Cape.
  • D. Buck Rogers
    Buck Rogers is a pioneering science fiction hero who popularized space adventure in early 20th-century American comics, radio, film serials, and television.
  • E. Dr. John Carter
    Dr. John Carter is a central fictional physician on the long-running medical drama series "ER," known for his evolution from idealistic medical student to seasoned doctor.
  • 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_69d822e6f1c88190bc494d491a907114 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dec72ea9348190817efcdaa973d7f7 completed April 14, 2026, 11:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69fdfb8bcc188190901e3f692fd8fbf9 completed May 8, 2026, 3:04 p.m.
Created at: April 10, 2026, 1:29 a.m.