Triple

T9839565
Position Surface form Disambiguated ID Type / Status
Subject John Q E239186 entity
Predicate composer P1361 FINISHED
Object Aaron Zigman E118675 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 Zigman | Statement: [John Q, composer, Aaron Zigman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aaron Zigman
Context triple: [John Q, composer, Aaron Zigman]
  • A. Aaron Zigman chosen
    Aaron Zigman is an American composer and producer best known for his film scores on dramas and romantic films such as "The Notebook" and "John Q."
  • B. Scott Gilman
    Scott Gilman is a musician best known as a member of the British-American rock band Foreigner.
  • C. Sam Koppelman
    Sam Koppelman is an American writer and political speechwriter known for co-authoring books with figures like Beto O’Rourke and for his work on voting rights and democracy.
  • D. Mitchell Hurwitz
    Mitchell Hurwitz is an American television writer and producer best known for creating the critically acclaimed sitcom "Arrested Development."
  • E. Lee Eisenberg
    Lee Eisenberg is an American television writer and producer best known for his work on series such as The Office and Hello Ladies.
  • 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_69ca84e3f0c48190ada72a65ebd50efd completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdb34b045481908f89abd576aab497 completed April 2, 2026, 12:07 a.m.
NED1 Entity disambiguation (via context triple) batch_69d1d5d5484c8190a78ccd0e9816ba51 completed April 5, 2026, 3:24 a.m.
Created at: March 30, 2026, 8:33 p.m.