Triple

T6628262
Position Surface form Disambiguated ID Type / Status
Subject The Flight Attendant E149856 entity
Predicate starring P1507 FINISHED
Object Zosia Mamet E151339 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: Zosia Mamet | Statement: [The Flight Attendant, starring, Zosia Mamet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zosia Mamet
Context triple: [The Flight Attendant, starring, Zosia Mamet]
  • A. Zosia Mamet chosen
    Zosia Mamet is an American actress best known for her role as the eccentric and fast-talking Shoshanna Shapiro on the HBO series "Girls."
  • B. Olivia Mazursky
    Olivia Mazursky is a member of the Mazursky family connected to Zack Mazursky, a figure known from the real-life kidnapping and murder case that inspired the film "Alpha Dog."
  • C. Ronit Matalon
    Ronit Matalon was an Israeli author known for her innovative Hebrew prose that explored themes of identity, family, and Mizrahi experience in contemporary Israeli society.
  • D. Gail Lumet Buckley
    Gail Lumet Buckley is an American author and journalist known for her historical writings on African American families and her memoirs reflecting on race, politics, and legacy.
  • E. Jenny Lumet
    Jenny Lumet is an American screenwriter and actress best known for writing the film "Rachel Getting Married" and for her work on several prominent television series.
  • 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_69c687ee50048190aa151765bef16193 completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6afa2e4a48190ba3c70013bab14f2 completed March 27, 2026, 4:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cbeb04348190957b8e5f098b72bf completed March 27, 2026, 6:26 p.m.
Created at: March 27, 2026, 1:59 p.m.