Triple

T5780339
Position Surface form Disambiguated ID Type / Status
Subject Jay Gould E127539 entity
Predicate notableChild P367 FINISHED
Object Helen Gould E248159 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: Helen Gould | Statement: [Jay Gould, notableChild, Helen Gould]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Helen Gould
Context triple: [Jay Gould, notableChild, Helen Gould]
  • A. Helen Gould chosen
    Helen Gould was a prominent American philanthropist and daughter of railroad magnate Jay Gould, known for her extensive charitable work in the late 19th and early 20th centuries.
  • B. Helen Wright
    Helen Wright is a wealthy, emotionally volatile socialite who becomes romantically entangled with a young violin prodigy in the film "Humoresque."
  • C. Helen Hughes
    Helen Hughes was a daughter of Charles Evans Hughes, the prominent American statesman who served as both U.S. Secretary of State and Chief Justice of the Supreme Court.
  • D. Helene Bradley
    Helene Bradley is a fictional character appearing in Ernest Hemingway’s novel "To Have and Have Not."
  • E. Helen Marshall
    Helen Marshall is a British academic leader and higher education administrator who has served as Vice-Chancellor of the University of Salford.
  • 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_69c008361fa88190aefa4dc41b051e7f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c029e3f88c8190975921ff2912e543 completed March 22, 2026, 5:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69c9251db3388190b8b0ac7549647887 completed March 29, 2026, 1:11 p.m.
Created at: March 22, 2026, 3:50 p.m.