Triple

T7396404
Position Surface form Disambiguated ID Type / Status
Subject Deadpool 2 E170631 entity
Predicate castMember P1668 FINISHED
Object Zazie Beetz E195731 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: Zazie Beetz | Statement: [Deadpool 2, castMember, Zazie Beetz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zazie Beetz
Context triple: [Deadpool 2, castMember, Zazie Beetz]
  • A. Zazie Beetz chosen
    Zazie Beetz is a German-American actress known for her roles in the TV series "Atlanta" and films such as "Deadpool 2" and "Joker."
  • B. Yaya DaCosta
    Yaya DaCosta is an American actress and model known for her work in film, television, and fashion, including roles in "America's Next Top Model," "The Butler," and "Chicago Med."
  • C. Awkwafina
    Awkwafina is an American actress, comedian, and rapper known for her breakout roles in films like "Crazy Rich Asians" and "The Farewell," as well as her distinctive comedic persona.
  • D. Leslie Jones
    Leslie Jones is an American film editor known for her work on major Hollywood productions, including the feature film "Starsky & Hutch."
  • E. Beanie Feldstein
    Beanie Feldstein is an American actress known for her comedic and dramatic roles in films such as "Booksmart" and "Lady Bird," as well as on Broadway.
  • 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_69c68a5f04188190ac266569c9280347 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f248f79c819094b1d1e2c3d511d1 completed March 27, 2026, 9:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c82772400881908d6b11b60a1443bb completed March 28, 2026, 7:09 p.m.
Created at: March 27, 2026, 3:09 p.m.