Triple

T8002333
Position Surface form Disambiguated ID Type / Status
Subject Maggie Gyllenhaal E186279 entity
Predicate mother P120 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: [Maggie Gyllenhaal, mother, Naomi Foner]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Naomi Foner
Context triple: [Maggie Gyllenhaal, mother, 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. 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.
  • C. 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.
  • D. Kathleen Middlekauff
    Kathleen Middlekauff is an American academic and former spouse of investigative journalist and author Bob Woodward.
  • E. Margaret Pomeranz
    Margaret Pomeranz is an Australian film critic and television presenter best known for co-hosting long-running movie review programs such as "The Movie Show" and "At the Movies."
  • 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_69ca82aaaf24819084b94d18f699ba53 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb3cf2918081909ee0afab11caed63 completed March 31, 2026, 3:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69cbe11aefc88190bcf614e936455927 completed March 31, 2026, 2:58 p.m.
Created at: March 30, 2026, 5:18 p.m.