Triple

T3996209
Position Surface form Disambiguated ID Type / Status
Subject Ocean's 8 E87102 entity
Predicate castMember P1668 FINISHED
Object Awkwafina E390743 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: Awkwafina | Statement: [Ocean's 8, castMember, Awkwafina]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Awkwafina
Context triple: [Ocean's 8, castMember, Awkwafina]
  • A. Awkwafina chosen
    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.
  • B. Zazie Beetz
    Zazie Beetz is a German-American actress known for her roles in the TV series "Atlanta" and films such as "Deadpool 2" and "Joker."
  • C. Constance Wu
    Constance Wu is an American actress best known for her starring roles in the TV series "Fresh Off the Boat" and the film "Crazy Rich Asians."
  • D. Natasha Lyonne
    Natasha Lyonne is an American actress, writer, and director known for her distinctive raspy voice and roles in projects like Russian Doll, the American Pie films, and various acclaimed independent movies.
  • E. Leslie Jones
    Leslie Jones is an American film editor known for her work on major Hollywood productions, including the feature film "Starsky & Hutch."
  • 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_69aed94118148190975e6aa4e554cde9 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa2159d88190a01de8b038341916 completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5403f14ec8190a77189c7066676f2 completed March 14, 2026, 11:02 a.m.
Created at: March 9, 2026, 3:34 p.m.