Triple

T10072914
Position Surface form Disambiguated ID Type / Status
Subject Jascha Brodsky E213672 entity
Predicate notableStudent P4838 FINISHED
Object Aaron Rosand E825679 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: Aaron Rosand | Statement: [Jascha Brodsky, notableStudent, Aaron Rosand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aaron Rosand
Context triple: [Jascha Brodsky, notableStudent, Aaron Rosand]
  • A. Aaron Rosand chosen
    Aaron Rosand was an American violinist renowned for his Romantic repertoire, rich tone, and influential teaching career at the Curtis Institute of Music.
  • B. Marc Roskin
    Marc Roskin is a television producer and director best known for his work on genre and adventure series such as "The Librarians."
  • C. Eric Tannenbaum
    Eric Tannenbaum is a television producer best known for his work on popular American sitcoms, including serving as an executive producer on "Two and a Half Men."
  • D. Aaron Mendelsohn
    Aaron Mendelsohn is an American screenwriter best known for co-writing the family sports film "Air Bud" and working extensively in film and television.
  • E. Michael Aronov
    Michael Aronov is an American actor known for his work in film, television, and theater, including a role in the historical drama "Operation Finale."
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd013c9d0819091ebe6fc399832de completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbd9073c948190aa2e9e6b7ffe9022 completed April 12, 2026, 5:40 p.m.
Created at: March 30, 2026, 8:59 p.m.