Triple

T18181407
Position Surface form Disambiguated ID Type / Status
Subject Michael Eisner E435292 entity
Predicate birthName P65 FINISHED
Object Michael Dammann Eisner 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: Michael Dammann Eisner | Statement: [Michael Eisner, birthName, Michael Dammann Eisner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Dammann Eisner
Context triple: [Michael Eisner, birthName, Michael Dammann Eisner]
  • A. Michael Eisner chosen
    Michael Eisner is an American businessman and former longtime CEO of The Walt Disney Company, known for overseeing its major expansion in the late 20th century.
  • B. Eric Eisner
    Eric Eisner is a film producer best known for his work on independent and offbeat movies, including the comedy "Hamlet 2."
  • C. Terry Semel
    Terry Semel is an American media executive best known as the former CEO and Chairman of Yahoo! and longtime Warner Bros. studio chief.
  • D. Donald Zucker
    Donald Zucker is an American real estate developer and philanthropist whose major donations to education and healthcare have led to prominent institutions bearing his name.
  • E. Stephen A. Ross
    Stephen A. Ross was an influential American economist and financial theorist best known for developing the arbitrage pricing theory and making foundational contributions to modern finance.
  • 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_69d8b90c7ec081909b4694ccecb449c6 completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e4dffb3bc88190a627be9c444d5c7d completed April 19, 2026, 2 p.m.
Created at: April 10, 2026, 10:31 a.m.