Triple
T19647973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Shack |
E471729
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Radha Mitchell |
—
|
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: Radha Mitchell | Statement: [The Shack, stars, Radha Mitchell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Radha Mitchell Context triple: [The Shack, stars, Radha Mitchell]
-
A.
Radha Mitchell
chosen
Radha Mitchell is an Australian actress known for her versatile performances in independent films and Hollywood productions, including notable roles in dramas, thrillers, and horror films.
-
B.
Emily Patterson
Emily Patterson is the daughter of American actress Téa Leoni.
-
C.
Cristin Milioti
Cristin Milioti is an American actress and singer known for her work in film, television, and theater, including roles in "How I Met Your Mother," "The Wolf of Wall Street," and "Palm Springs."
-
D.
Carrie Coon
Carrie Coon is an American actress known for her acclaimed performances in television series like "The Leftovers" and "Fargo" as well as films such as "Gone Girl" and "The Nest."
-
E.
Emma Mackey
Emma Mackey is a French-British actress best known for her breakout role in the Netflix series "Sex Education" and for appearing in high-profile films such as "Barbie" and "Death on the Nile."
- 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_69d8e51395348190ac1416d46dfc6db0 |
completed | April 10, 2026, 11:54 a.m. |
| NER | Named-entity recognition | batch_69e64126cea88190a1a6929f46de4686 |
completed | April 20, 2026, 3:07 p.m. |
Created at: April 10, 2026, 1:44 p.m.