Triple

T2462065
Position Surface form Disambiguated ID Type / Status
Subject Get Out E54553 entity
Predicate hasCastMember P2308 FINISHED
Object Daniel Kaluuya E130653 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: Daniel Kaluuya | Statement: [Get Out, hasCastMember, Daniel Kaluuya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Daniel Kaluuya
Context triple: [Get Out, hasCastMember, Daniel Kaluuya]
  • A. Daniel Kaluuya chosen
    Daniel Kaluuya is a British actor acclaimed for his powerful performances in films such as "Get Out," "Black Panther," and "Judas and the Black Messiah."
  • B. Yahya Abdul-Mateen II
    Yahya Abdul-Mateen II is an American actor known for his roles in major films and TV series such as "Aquaman," "Watchmen," and "Candyman."
  • C. Mahershala Ali
    Mahershala Ali is an American actor acclaimed for his powerful performances in films and television, earning multiple Academy Awards and widespread recognition for his nuanced, character-driven roles.
  • D. David Oyelowo
    David Oyelowo is a British-Nigerian actor known for his powerful performances in film and television, particularly in biographical and historical dramas.
  • E. Aldis Hodge
    Aldis Hodge is an American actor known for his versatile film and television roles, including prominent performances in projects like "Leverage," "One Night in Miami...," and "Black Adam."
  • 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_69ab49dee84c819096b50a0049c347ac completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd11f093c8190877db3026d430bd5 completed March 7, 2026, 7:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69aef0d561a081909310113658b98f12 completed March 9, 2026, 4:09 p.m.
Created at: March 6, 2026, 9:44 p.m.