Triple
T7837240
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Great Gatsby (2013 film) |
E181716
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Carey Mulligan |
E216276
|
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: Carey Mulligan | Statement: [The Great Gatsby (2013 film), starring, Carey Mulligan]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Carey Mulligan Context triple: [The Great Gatsby (2013 film), starring, 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.
Gemma Arterton
Gemma Arterton is an English actress known for her roles in films such as "St Trinian's," "Quantum of Solace," and "Prince of Persia: The Sands of Time."
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c203b4819099c039c617628927 |
completed | March 31, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5aad325c8190bced57e8380bc729 |
completed | March 31, 2026, 5:25 a.m. |
Created at: March 30, 2026, 4:46 p.m.