Triple

T4170850
Position Surface form Disambiguated ID Type / Status
Subject Rising Star Award E84557 entity
Predicate notableRecipient P108 FINISHED
Object Emma Mackey E252080 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: Emma Mackey | Statement: [Rising Star Award, notableRecipient, Emma Mackey]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Emma Mackey
Context triple: [Rising Star Award, notableRecipient, Emma Mackey]
  • A. Emma Mackey chosen
    Emma Mackey is a French-British actress best known for her breakout role in the Netflix series "Sex Education" and for appearing in high-profile films such as "Barbie" and "Death on the Nile."
  • B. Cailee Spaeny
    Cailee Spaeny is an American actress known for her breakout role in the science fiction film "Pacific Rim: Uprising" and subsequent performances in both film and television.
  • C. Olivia Cooke
    Olivia Cooke is an English actress known for her roles in films like "Ready Player One" and the TV series "Bates Motel" and "House of the Dragon."
  • D. Natalia Dyer
    Natalia Dyer is an American actress best known for her role as Nancy Wheeler in the Netflix science fiction-horror series "Stranger Things."
  • E. Eliza Scanlen
    Eliza Scanlen is an Australian actress known for her roles in film and television, including prominent performances in projects like "Sharp Objects" and "Little Women."
  • 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_69aed932cab48190b80ffe35f7029ae1 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af02c87cc88190a9ec3712db18a8a7 completed March 9, 2026, 5:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7045bf08190a5d2bab75a2240d4 completed March 14, 2026, 8:37 p.m.
Created at: March 9, 2026, 3:45 p.m.