Triple
T19982914
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Brooklyn (2015 film) |
E493861
|
entity |
| Predicate | portrayedBy |
P1507
|
FINISHED |
| Object | Saoirse Ronan |
—
|
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: Saoirse Ronan | Statement: [Brooklyn (2015 film), portrayedBy, Saoirse Ronan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saoirse Ronan Context triple: [Brooklyn (2015 film), portrayedBy, Saoirse Ronan]
-
A.
Saoirse Ronan
chosen
Saoirse Ronan is an acclaimed Irish-American actress known for her nuanced performances in films such as "Atonement," "Brooklyn," "Lady Bird," and "Little Women."
-
B.
Carey Mulligan
Carey Mulligan is an acclaimed British actress known for her performances in films such as "An Education," "Drive," and "Promising Young Woman."
-
C.
Emma D'Arcy
Emma D'Arcy is a British actor best known for their leading role as Rhaenyra Targaryen in the HBO series "House of the Dragon."
-
D.
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."
-
E.
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.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d14c3c08190b1ba8f4da08a4ccf |
completed | April 20, 2026, 5:06 p.m. |
Created at: April 11, 2026, 3:28 p.m.