Triple
T4861391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Grace Marks |
E108666
|
entity |
| Predicate | portrayedBy |
P1507
|
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: [Grace Marks, portrayedBy, Sarah Gadon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarah Gadon Context triple: [Grace Marks, portrayedBy, 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.
Maria Riva
Maria Riva is a German-American actress and author best known as the daughter and biographer of film legend Marlene Dietrich.
-
D.
Olivia Cooke
Olivia Cooke is an English actress known for her roles in films like "Ready Player One" and the TV series "Bates Motel" and "House of the Dragon."
-
E.
Nathalie Emmanuel
Nathalie Emmanuel is a British actress best known for her roles as Missandei in "Game of Thrones" and Ramsey in the "Fast & Furious" film franchise.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5f62b48190b367ed1b850cfbcb |
completed | March 20, 2026, 3:53 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cf921cc8190a092bb69c1981890 |
completed | March 21, 2026, 8:55 a.m. |
Created at: March 20, 2026, 1:26 p.m.