Triple

T19982923
Position Surface form Disambiguated ID Type / Status
Subject Brooklyn (2015 film) E493861 entity
Predicate castMember P1668 FINISHED
Object Jessica Paré 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: Jessica Paré | Statement: [Brooklyn (2015 film), castMember, Jessica Paré]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jessica Paré
Context triple: [Brooklyn (2015 film), castMember, Jessica Paré]
  • A. Jessica Paré chosen
    Jessica Paré is a Canadian actress best known for her role as Megan Draper on the television series "Mad Men."
  • B. Vanessa Marcil
    Vanessa Marcil is an American actress best known for her roles on the television series "General Hospital," "Beverly Hills, 90210," and "Las Vegas."
  • C. Anna Paquin
    Anna Paquin is an Academy Award–winning Canadian-born New Zealand actress known for films such as "The Piano," the "X-Men" series, and the TV series "True Blood."
  • D. Kathrine Narducci
    Kathrine Narducci is an American actress best known for her roles in Italian-American crime dramas, including prominent parts in films and television series such as The Sopranos.
  • E. Lindsay Noseworth
    Lindsay Noseworth is a fictional aeronaut and member of the skyfaring boy-adventurer crew in Thomas Pynchon's "Chums of Chance" stories.
  • 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_69da626a67648190af9653832a3aeced completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e65d14c3c08190b1ba8f4da08a4ccf completed April 20, 2026, 5:06 p.m.
Created at: April 11, 2026, 3:28 p.m.