Triple
T30437986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Distant |
E774362
|
entity |
| Predicate | CannesBestActorRecipients |
P8115
|
FINISHED |
| Object | Muzaffer Özdemir |
—
|
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: Muzaffer Özdemir | Statement: [Distant, CannesBestActorRecipients, Muzaffer Özdemir]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: CannesBestActorRecipients Context triple: [Distant, CannesBestActorRecipients, Muzaffer Özdemir]
-
A.
yearOfAwardCannesBestActress
Indicates the specific year in which an individual received the Cannes Film Festival Best Actress award.
-
B.
cannesFilmFestivalAward
Indicates that an entity has received an award presented at the Cannes Film Festival.
-
C.
bestActorWinner
chosen
Indicates that the subject is the recipient of a "Best Actor" award for a particular performance or event.
-
D.
numberOfCésarAwardsForBestActress
Indicates the count of César Awards for Best Actress that have been received by a given entity.
-
E.
bestActorMotionPictureDramaWork
Indicates that a person received the award for best actor in a motion picture drama for a specific work.
- 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_69f22492d2a88190995ce8745d9becaa |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68696b51481908e337f6734102fea |
completed | May 2, 2026, 11:19 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 8:08 p.m.