Triple
T21991852
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One Day |
E543108
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Nina Jacobson |
—
|
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: Nina Jacobson | Statement: [One Day, producer, Nina Jacobson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nina Jacobson Context triple: [One Day, producer, Nina Jacobson]
-
A.
Nina Jacobson
chosen
Nina Jacobson is an American film and television producer best known as the founder of Color Force and for producing major franchises such as "The Hunger Games."
-
B.
Amy Pascal
Amy Pascal is an American film producer and former Sony Pictures executive known for overseeing and producing numerous major Hollywood films.
-
C.
Megan Ellison
Megan Ellison is an American film producer and founder of Annapurna Pictures, known for backing acclaimed independent and auteur-driven films such as "Her," "Zero Dark Thirty," and "American Hustle."
-
D.
Diane Mostow
Diane Mostow is a writer known for her work on the television series "Breakdown."
-
E.
Jane Kurson
Jane Kurson is a film editor best known for her work on the 1988 fantasy-comedy film "Beetlejuice."
- 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_69e0c48136b081908831fa907cc02e18 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f1270e951081908deda039b47ca84b |
completed | April 28, 2026, 9:30 p.m. |
Created at: April 16, 2026, 8:05 p.m.