Triple

T22448432
Position Surface form Disambiguated ID Type / Status
Subject Peter Drucker E554924 entity
Predicate familyName P18 FINISHED
Object Drucker NE NERFINISHED

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: Drucker | Statement: [Peter Drucker, familyName, Drucker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Drucker
Context triple: [Peter Drucker, familyName, Drucker]
  • A. Drucker chosen
    Drucker is a surname of German origin borne by various notable individuals across fields such as economics, medicine, and the arts.
  • B. Peter Drucker
    Peter Drucker was a pioneering management theorist and author whose ideas on management by objectives, decentralization, and the role of the modern corporation profoundly shaped 20th-century business practice.
  • C. Philip Drucker
    Philip Drucker was an American anthropologist and archaeologist known for his pioneering fieldwork on Mesoamerican cultures, particularly the Olmec civilization.
  • D. Heilmeier
    Heilmeier is a German-language surname most notably associated with George Heilmeier, an American engineer and pioneer in liquid crystal display (LCD) technology.
  • E. Robert Katz
    Robert Katz is a film producer best known for his work on projects such as the 1993 historical war drama "Gettysburg."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e5113208190ab58c6b595f9d1d0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b4a20f8819097f471084e97e099 completed April 29, 2026, 1:13 a.m.
Created at: April 16, 2026, 8:48 p.m.