Triple
T29894003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Best Intentions |
E759227
|
entity |
| Predicate | leadActressAwardReceived |
P6108
|
FINISHED |
| Object | Best Actress at Cannes Film Festival |
—
|
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: Best Actress at Cannes Film Festival | Statement: [The Best Intentions, leadActressAwardReceived, Best Actress at Cannes Film Festival]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: leadActressAwardReceived Context triple: [The Best Intentions, leadActressAwardReceived, Best Actress at Cannes Film Festival]
-
A.
leadingActressNominee
Indicates that a person has been nominated for an award in the leading actress category for a particular work or performance.
-
B.
leadActorAwarded
Indicates that the person in the lead actor role has received an award for their performance.
-
C.
leadActress
chosen
Indicates that the subject is the primary female performer in the specified film, show, or production.
-
D.
leadActorNominee
Indicates that an entity was nominated for a lead acting role in relation to a particular work or award.
-
E.
bestActressWinner
Indicates that the subject has won the Best Actress award in a given competition or context.
- 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_69f2245f1cf88190978c70d1a1d2cb73 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 29, 2026, 6:03 p.m.