Triple

T15389275
Position Surface form Disambiguated ID Type / Status
Subject Very Good Girls E367996 entity
Predicate director P255 FINISHED
Object Naomi Foner E534024 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: Naomi Foner | Statement: [Very Good Girls, director, Naomi Foner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naomi Foner
Context triple: [Very Good Girls, director, Naomi Foner]
  • A. Naomi Foner chosen
    Naomi Foner is an American screenwriter and film producer best known for writing the acclaimed drama "Running on Empty" and for being the mother of actors Maggie and Jake Gyllenhaal.
  • B. Mildred Wilentz
    Mildred Wilentz was an American editor and publisher known for her influential work in mid-20th-century literary and political publishing circles.
  • C. Barbara Franklin
    Barbara Franklin is an American business executive and former U.S. Secretary of Commerce known for advancing women’s roles in government and corporate leadership.
  • D. Kathleen Buhle
    Kathleen Buhle is an American nonprofit executive and author best known as the ex-wife of Hunter Biden and for her memoir detailing their marriage and divorce.
  • E. Kathleen Middlekauff
    Kathleen Middlekauff is an American academic and former spouse of investigative journalist and author Bob Woodward.
  • 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_69d85a1551a08190ba2caea7cd51c639 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e761b688190893a81246b735b76 completed April 16, 2026, 1:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff134e37d881909f373b90a99fc067 completed May 9, 2026, 10:58 a.m.
Created at: April 10, 2026, 3:19 a.m.