Triple

T4880007
Position Surface form Disambiguated ID Type / Status
Subject Yuja Wang E109299 entity
Predicate studiedUnder P7251 FINISHED
Object Gary Graffman E213668 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: Gary Graffman | Statement: [Yuja Wang, studiedUnder, Gary Graffman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gary Graffman
Context triple: [Yuja Wang, studiedUnder, Gary Graffman]
  • A. Gary Graffman chosen
    Gary Graffman is an American classical pianist, renowned pedagogue, and former president of the Curtis Institute of Music who has taught many leading pianists of his generation.
  • B. Andrew Scheinman
    Andrew Scheinman is an American film and television producer and director best known for his work on popular comedies such as "When Harry Met Sally..." and his collaborations with Rob Reiner.
  • C. James Altman
    James Altman is the son of American lawyer and video game executive Robert A. Altman.
  • D. Douglas Shulman
    Douglas Shulman is an American public official who served as the head of the U.S. Internal Revenue Service (IRS) during the late 2000s and early 2010s.
  • E. Steven Baigelman
    Steven Baigelman is an American screenwriter and producer known for his work on biographical and crime dramas in film and television.
  • 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_69bd440e9d64819083e82cf33b4d9570 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd6dc071d4819083ea9fd0c73c5f49 completed March 20, 2026, 3:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69be6803a1c081908972984241276c19 completed March 21, 2026, 9:42 a.m.
Created at: March 20, 2026, 1:27 p.m.