Triple
T7049366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Nun's Story |
E163724
|
entity |
| Predicate | leadActorPerformanceReception |
P52442
|
FINISHED |
| Object | praised as powerful and restrained |
—
|
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: praised as powerful and restrained | Statement: [The Nun's Story, leadActorPerformanceReception, praised as powerful and restrained]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActorPerformanceReception Context triple: [The Nun's Story, leadActorPerformanceReception, praised as powerful and restrained]
-
A.
leadActorBreakthrough
Indicates that the actor had a breakthrough or career-defining leading role in the referenced work or context.
-
B.
leadActorAwarded
Indicates that the person in the lead actor role has received an award for their performance.
-
C.
leadActorNominee
Indicates that an entity was nominated for a lead acting role in relation to a particular work or award.
-
D.
starredActor
Indicates that an actor performed a leading or significant role in a particular production or work.
-
E.
portrayalReception
chosen
Indicates how a particular portrayal of someone or something is received, evaluated, or responded to by an audience or observers.
- F. None of above.
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_69c6885f598c8190b6b6495c59d8d962 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e4a3c36c819080942c59f1830ae8 |
completed | March 27, 2026, 8:12 p.m. |
| PD | Predicate disambiguation | batch_69c6e1bb602081908bfa6186a1f5a4b4 |
completed | March 27, 2026, 7:59 p.m. |
Created at: March 27, 2026, 2:37 p.m.