Triple
T22395511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ouija |
E553618
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Olivia Cooke |
—
|
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: Olivia Cooke | Statement: [Ouija, stars, Olivia Cooke]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivia Cooke Context triple: [Ouija, stars, Olivia Cooke]
-
A.
Olivia Cooke
chosen
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."
-
B.
Kyliegh Curran
Kyliegh Curran is an American actress best known for her roles in the horror film "Doctor Sleep" and the Netflix series "The Fall of the House of Usher."
-
C.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
D.
Olivia DeJonge
Olivia DeJonge is an Australian actress known for her role as Priscilla Presley in Baz Luhrmann’s 2022 biographical film "Elvis."
-
E.
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."
- 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_69e11e4cf87c8190a1ff474daec326b7 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1585e84b081908c95ed3e0d987ed8 |
completed | April 29, 2026, 1:01 a.m. |
Created at: April 16, 2026, 8:45 p.m.