Triple
T9790033
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nut Job |
E237582
|
entity |
| Predicate | voiceCastMember |
P9616
|
FINISHED |
| Object | Sarah Gadon |
E467333
|
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: Sarah Gadon | Statement: [The Nut Job, voiceCastMember, Sarah Gadon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Gadon Context triple: [The Nut Job, voiceCastMember, Sarah Gadon]
-
A.
Sarah Gadon
chosen
Sarah Gadon is a Canadian actress known for her work in film and television, including prominent roles in period dramas and genre movies.
-
B.
Isabelle Nélisse
Isabelle Nélisse is a Canadian actress known for her roles in psychologically intense films and television series, often portraying complex and troubled young characters.
-
C.
Radha Mitchell
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.
-
D.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
E.
Madeleine Lesser
Madeleine Lesser is the wife of British actor Anton Lesser, known for his work in television, film, and theatre.
- 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_69ca84dc04488190b9c91193976c0960 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda214875481909f39e1d4dbac1fdb |
completed | April 1, 2026, 10:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1cc4e30bc81909b1dce4a0cc69991 |
completed | April 5, 2026, 2:43 a.m. |
Created at: March 30, 2026, 8:28 p.m.