Triple

T21329142
Position Surface form Disambiguated ID Type / Status
Subject Anne Bancroft E525849 entity
Predicate hasPseudonym P3799 FINISHED
Object Anne Marno NE NERFINISHED

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: Anne Marno | Statement: [Anne Bancroft, hasPseudonym, Anne Marno]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anne Marno
Context triple: [Anne Bancroft, hasPseudonym, Anne Marno]
  • A. Anne Marno chosen
    Anne Marno is an alternate professional name used by the acclaimed American actress Anne Bancroft, known for her powerful performances on stage and screen.
  • B. Mary Looram
    Mary Looram is an actress known for her role in the film "Like Father."
  • C. Anne Manson
    Anne Manson is an American conductor known for her leadership roles with major orchestras and opera companies in the United States and Europe.
  • D. Adrienne Marden
    Adrienne Marden was an American character actress known for her supporting roles in mid-20th-century film and television.
  • E. Johanna Jarman
    Johanna Jarman is known as the wife of former child actor Claude Jarman Jr., who gained fame for his Academy Award-winning role in the 1946 film "The Yearling."
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b51b90788190a4dd823d962626da completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7ab4f95fc819087eb32dca7da689a completed April 21, 2026, 4:52 p.m.
Created at: April 16, 2026, 4:42 p.m.