Triple
T20387469
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don't Make Me Go |
E497995
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Kaya Scodelario |
—
|
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: Kaya Scodelario | Statement: [Don't Make Me Go, starring, Kaya Scodelario]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaya Scodelario Context triple: [Don't Make Me Go, starring, Kaya Scodelario]
-
A.
Kaya Scodelario
chosen
Kaya Scodelario is an English actress known for her breakout role in the TV series "Skins" and for starring in major film franchises such as "The Maze Runner" and "Pirates of the Caribbean."
-
B.
Katherine Hoult
Katherine Hoult is known as the spouse of Richard Mather.
-
C.
Rosanna Hoult
Rosanna Hoult is a British actress known for her work in film and television and as the sister of actor Nicholas Hoult.
-
D.
Shailene Woodley
Shailene Woodley is an American actress known for her breakout role in "The Descendants" and for starring in films such as "The Fault in Our Stars" and the "Divergent" series.
-
E.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
- 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_69e0b4a71ebc8190b153a36c738730f4 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6790c935881908f901d058e6a83a9 |
completed | April 20, 2026, 7:05 p.m. |
Created at: April 16, 2026, 11:28 a.m.