Triple

T18627056
Position Surface form Disambiguated ID Type / Status
Subject Terrence Kaufman E455310 entity
Predicate familyName P18 FINISHED
Object Kaufman 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: Kaufman | Statement: [Terrence Kaufman, familyName, Kaufman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kaufman
Context triple: [Terrence Kaufman, familyName, Kaufman]
  • A. Kaufman chosen
    Kaufman is a surname most famously associated with American playwright and director George S. Kaufman, known for his sharp wit and influential contributions to 20th-century theater.
  • B. Kaufman
    Kaufman is a small suburban city within the Dallas–Fort Worth metropolitan area in Texas, known for its rural character and proximity to the larger urban core.
  • C. Kaufmann
    Kaufmann is a German surname borne by numerous individuals, including the renowned operatic tenor Jonas Kaufmann.
  • D. Kaminsky
    Kaminsky is the original family surname of American entertainer Danny Kaye, born David Daniel Kaminsky.
  • E. Korman
    Korman is a surname most famously associated with American comedic actor Harvey Korman, known for his work on The Carol Burnett Show and in Mel Brooks films.
  • 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_69d8d38cc7948190a55ea64e5638994e completed April 10, 2026, 10:40 a.m.
NER Named-entity recognition batch_69e54f0581f0819083c1aba9fb85f6a7 completed April 19, 2026, 9:54 p.m.
Created at: April 10, 2026, 11:46 a.m.