Triple
T13549434
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nicole Kidman as Sue Brierley |
E323601
|
entity |
| Predicate | academyAwardsContext |
P110302
|
FINISHED |
| Object | part of Lion’s Best Picture–nominated ensemble |
—
|
LITERAL 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: part of Lion’s Best Picture–nominated ensemble | Statement: [Nicole Kidman as Sue Brierley, academyAwardsContext, part of Lion’s Best Picture–nominated ensemble]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: academyAwardsContext Context triple: [Nicole Kidman as Sue Brierley, academyAwardsContext, part of Lion’s Best Picture–nominated ensemble]
-
A.
academyAwardsEdition
Indicates the specific edition or installment of the Academy Awards associated with an entity.
-
B.
AcademyAwardsYear
Indicates the specific year in which the referenced Academy Awards event took place.
-
C.
oscarAward
Indicates that an entity has received or been honored with an Academy Award (Oscar).
-
D.
academyAwardNominations
Indicates that an entity has received one or more nominations for an Academy Award (Oscars).
-
E.
academyAwardWins
Indicates that one entity has won a specified number of Academy Awards (Oscars) or that a winning relationship exists between the entity and the Academy Award.
- F. None of above. chosen
Provenance (4 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_69d8076776248190bdf0d4fa1f85a5fc |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae13bec4819084c1770638c00ed9 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbbb8c77dc8190b7bd803b5e168d23 |
completed | April 12, 2026, 3:34 p.m. |
Created at: April 9, 2026, 9:46 p.m.