Triple

T1093368
Position Surface form Disambiguated ID Type / Status
Subject Ziegfeld Girl E24216 entity
Predicate screenwriter P2831 FINISHED
Object Sonya Levien E139994 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: Sonya Levien | Statement: [Ziegfeld Girl, screenwriter, Sonya Levien]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sonya Levien
Context triple: [Ziegfeld Girl, screenwriter, Sonya Levien]
  • A. Sonya Levien chosen
    Sonya Levien was a prominent American screenwriter known for her work on numerous Hollywood films from the silent era through the 1950s, often adapting literary and theatrical works for the screen.
  • B. Tatiana Schlossberg
    Tatiana Schlossberg is an American journalist and author, known for her environmental reporting and as a member of the Kennedy family.
  • C. Nina Bernstein
    Nina Bernstein is the daughter of renowned American composer and conductor Leonard Bernstein, known for helping preserve and promote her father's musical legacy.
  • D. Sandra Levy
    Sandra Levy is an Australian film producer known for her work on acclaimed features such as the 1987 drama "High Tide."
  • E. Julia Bloch
    Julia Bloch is an American poet, editor, and scholar known for her innovative work in contemporary poetry and literary criticism.
  • 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_69a4940542308190ac2a0b1f730b7cfc completed March 1, 2026, 7:31 p.m.
NER Named-entity recognition batch_69a4b99bd06c8190bce1d77b0337b07c completed March 1, 2026, 10:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69adf3a5cac081908d655e42a58a81c5 completed March 8, 2026, 10:09 p.m.
Created at: March 1, 2026, 7:42 p.m.