Triple
T23407207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Maestro (2023 film) |
E559965
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Carey Mulligan |
—
|
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: Carey Mulligan | Statement: [Maestro (2023 film), castMember, Carey Mulligan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carey Mulligan Context triple: [Maestro (2023 film), castMember, Carey Mulligan]
-
A.
Carey Mulligan
chosen
Carey Mulligan is an acclaimed British actress known for her performances in films such as "An Education," "Drive," and "Promising Young Woman."
-
B.
Lucy Boynton
Lucy Boynton is a British-American actress known for her roles in films such as "Bohemian Rhapsody" and "Sing Street," as well as various television dramas.
-
C.
Rooney Mara
Rooney Mara is an American actress known for her acclaimed performances in films such as "The Girl with the Dragon Tattoo" and "Carol."
-
D.
Saoirse Ronan
Saoirse Ronan is an acclaimed Irish-American actress known for her nuanced performances in films such as "Atonement," "Brooklyn," "Lady Bird," and "Little Women."
-
E.
Danielle Macdonald
Danielle Macdonald is an Australian actress known for her breakout roles in films such as "Patti Cake$," "Dumplin'," and the drama "Skin."
- 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_69e2454b3a5881909c64773dc8a5d289 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1a50e607c8190ba0a22e89862a2d9 |
completed | April 29, 2026, 6:28 a.m. |
Created at: April 17, 2026, 5:38 p.m.